Mid-Level Python Engineer – Trading Systems & Data Pipelines

🏢 Summary: Mid-Level Python Engineer role focused on building and optimizing data pipelines and analytical frameworks for trading systems in a high-performance, live market environment. The position involves processing large-scale trading data, improving execution quality, and supporting real-time monitoring within the trading stack. This is an on-site opportunity in Wroclaw with direct impact on trading efficiency and market transparency. 🗂️ Requirements: 7+ years of professional Python development experience, Experience building libraries, data platforms, or analytical tooling, Strong experience with large-scale and time series datasets, Proficiency with NumPy and Pandas, Solid SQL knowledge, Experience with analytical databases, Experience working in Linux environments, Experience with testing, version control, and CI, Fluent English, Legal right to work in the European Union 📃 Skills: Python, NumPy, Pandas, SQL, Linux, CI, Git, C, C++, Rust 🏢 Description: Empower the future of trading technology — design innovative data pipelines and analytics that revolutionize market microstructure! Wroclaw-based opportunity with on-site work model. As a Mid-Level Python Engineer – Trading Systems & Data Pipelines , you will be working for our client, a leading financial technology firm specializing in trading infrastructure. You will help build and enhance systems that analyze trading behavior, optimize execution strategies, and support high-performance live trading environments. This is a chance to directly impact the efficiency and transparency of global markets through cutting-edge engineering. Your main responsibilities: Develop Python libraries, data pipelines, and tooling to process exchange protocols, order flow, and large-scale trading data. Design analytical frameworks, metrics, and monitoring tools to evaluate execution quality and system performance. Operate close to the trading stack, working with high-resolution datasets for research and production use. Collaborate with stakeholders to translate analytical insights into measurable improvements in trading execution. Support live trading systems through data validation, pipeline reliability, and real-time monitoring. Analyze trading behavior across venues to identify inefficiencies and improve latency and fill performance. Work with research and infrastructure teams to support ongoing development of market behavior understanding. You're ideal for this role if you have: 7+ years of professional experience in Python development, building libraries, data platforms, or analytical tooling. Strong experience working with large-scale and time series datasets using tools such as NumPy and Pandas. Solid SQL knowledge and experience working with analytical databases. Excellent problem-solving skills and the ability to investigate complex data and system behaviors. Ability to translate analytical or trading-related problems into robust engineering solutions. Experience working in Linux environments, following best practices like testing, version control, and CI. Strong communication skills for collaborating across technical and non-technical teams. Familiarity with financial markets, electronic trading, or execution analysis. It is a strong plus if you have: Exposure to network protocols, packet analysis, or performance optimization techniques. Experience with lower-level programming languages such as C, C++, or Rust. Language Required for the role: Fluent English Eligibility for the role: Only candidates with an existing legal right to work in the European Union will be considered for this role. #MAKEYourCareerBETTER

🏢 Summary: Senior Python Developer role focused on building high-performance data pipelines and monitoring solutions for low-latency trading systems. The position involves processing network packet data, developing analytics tools, and enhancing real-time trading infrastructure. It offers direct impact on trading performance within a financial technology environment. 🗂️ Requirements: Minimum 3 years of software development experience, Professional experience with Python, Experience with Shell scripting, Experience in data analytics and time series analysis, Basic knowledge of TCP/IP, UDP and Ethernet protocols, Understanding of GNU/Linux kernel and OS internals, Basic knowledge of C/C++, Fluent English, Legal right to work in the European Union 📃 Skills: Python, Shell, TCP/IP, UDP, Ethernet, Linux, GNU, C, C++, Analytics, TimeSeries 🏢 Description: Empower the Future of Trading — Shape High-Performance Data Pipelines in a Dynamic Financial Ecosystem! Wroclaw-based opportunity with on-site work model (5 on-site days per week allowed). As a Senior Python Developer – Trading Technology & Data Pipelines , you will be working for our client, a leading financial technology firm specializing in low-latency trading strategies. Join a team of innovative engineers and researchers dedicated to optimizing and transforming trading performance through cutting-edge data solutions and monitoring tools. This role offers a unique chance to directly influence trading outcomes and advance your career in financial technology. Your main responsibilities: Develop tools to collect and aggregate data from complex trading systems. Design and implement data pipelines to process network packet captures for low-latency network analysis. Build monitoring solutions with anomaly detection for network traffic and system metrics. Collaborate with the team to optimize trading strategies and improve system performance. Gain expertise in financial markets and trading technology while proposing measurable improvements. Contribute to high-performance data infrastructure supporting real-time trading decisions. Work closely with engineers to streamline data flows and enhance system reliability. You're ideal for this role if you have: At least 3 years of experience in software development, preferably in trading or finance. Strong proficiency in Python and Shell scripting. Experience in data analytics and time series analysis. Basic knowledge of TCP/IP, UDP, and Ethernet protocols. Understanding of GNU/Linux kernel and operating system internals. Fundamental knowledge of C/C++ programming. An interest in financial markets and trading technology. It is a strong plus if you have: (optional) Certifications or experience in network analysis or low-latency systems. Language Required for the role: Fluent in English, with excellent communication skills to collaborate effectively. Eligibility to work on this role: Only candidates with an existing legal right to work in the European Union will be considered for this role. #MAKEYourCareerBETTER Interested? Apply now and include your CV (preferably in English) along with a statement confirming your consent to the processing and storage of your personal data.

🏢 Summary: Mid-Level Python Systems Engineer role focused on building telemetry, diagnostics, and network analysis tools to enhance observability and performance of algorithmic trading systems. The position bridges software development, Linux systems, and networking to analyze low-level OS and network behavior in real time. You will develop data pipelines and automation tools to optimize trading infrastructure performance. 🗂️ Requirements: Minimum 3 years commercial experience with Python, Strong practical experience working in Linux environments, Understanding of OS internals: processes, memory, networking, Knowledge of TCP/IP, UDP, Ethernet, Multicast, Experience building and optimizing data pipelines, Ability to analyze raw network packet captures (PCAP), Practical Shell/Bash scripting skills, Basic ability to read C or C++ code 📃 Skills: Python, Linux, TCP/IP, UDP, Ethernet, Multicast, Bash, PCAP, Wireshark, tcpdump, C, C++ 🏢 Description: The Company: Our client is an innovative technology-driven trading firm operating globally. They are active players in the quantitative finance sector, known for leveraging massive datasets and advanced infrastructure. If you are passionate about computer systems engineering and want to dive into an environment where performance matters, this is a great place to grow. You will join a collaborative R&D team that builds and maintains the backbone of algorithmic trading systems. The Role: As a Mid-Level Python Systems Engineer, you will help bridge the gap between software development, network engineering, and data analysis. Working closely with senior engineers, your goal will be to enhance the observability and performance of the trading platform. Instead of writing trading strategies, you will help build the "eyes and ears" of the system—tools that allow the team to see exactly what is happening inside the network stack and the operating system in real-time. Key Responsibilities: System Telemetry & Tooling: Develop and maintain custom Python-based tools to harvest and aggregate telemetry data from distributed trading components. Network Analysis Pipelines: Build and optimize data pipelines specifically for processing raw network packet captures (PCAP) to analyze latency and throughput. Automated Diagnostics: Help create algorithms to detect anomalies in traffic patterns and OS performance metrics before they impact trading. Infrastructure Optimization: Collaborate with the team to analyze findings and recommend changes in the trading stack (e.g., kernel tuning, network config) to improve overall performance. Essential Skills: Python Experience: Minimum of 3 years of commercial experience writing clean, efficient, and robust Python code. Practical Linux Knowledge: You are comfortable working in a Linux environment and have a good understanding of how the OS handles processes, memory, and networking. An eagerness to learn more advanced concepts (like context switches or kernel bypass) is highly valued. Networking Fundamentals: Good understanding of the lower layers of the OSI model (TCP/IP, UDP, Ethernet, Multicast). Scripting: Practical knowledge of Shell/Bash for everyday automation tasks. Low-Level Awareness: Basic ability (or a strong willingness to learn how) to read C or C++ code to understand how Python interfaces with lower-level components. Desirable Experience (Nice to have): Background in analyzing large time-series datasets. Experience with network sniffing tools (Wireshark, tcpdump) and programmatic packet analysis. Previous exposure to FinTech, HFT, or electronic trading environments (though strong pure-tech candidates from other industries are very welcome!).

🏢 Summary: The offer is for a senior Python Developer role focused on building and optimizing trading systems, data pipelines, and analytical tools that enhance execution performance and market insights. The position centers on integrating with trading infrastructure, analyzing large-scale market data, and improving latency, fill rates, and execution quality. It involves close collaboration with research and infrastructure teams to deliver robust, real-time trading solutions. 🗂️ Requirements: Bachelor’s or advanced degree in Computer Science, Engineering, Mathematics, or related quantitative field, 7+ years of professional Python development experience, Experience building libraries, data platforms, or analytical tools, Experience with large-scale and time series datasets, Strong SQL knowledge and experience with analytical databases, Experience working in Linux environments, Knowledge of software engineering best practices (testing, version control, CI), Knowledge of financial markets and electronic trading, Ability to design and maintain real-time data pipelines and monitoring systems 📃 Skills: Python, SQL, NumPy, Pandas, Linux, Git, CI, C, C++, Rust 🏢 Description: About the Client Our client, a global leader in investment management, specializes in pioneering and data-centric strategies. The firm operates across all liquid asset classes globally, harnessing technology and data science to guide their investment strategies. The team comprises experts in data, technology, research, and trading who collaboratively tackle complex problems and achieve outstanding returns. Role Summary As a Python Developer, you'll be instrumental in developing systems and tools that integrate with the trading infrastructure and market mechanisms. Your duties will involve building data pipelines, analytical tools, and libraries to enhance execution analysis and trade performance. This role has been created due to the company's expansion and its objective of further refining trading capabilities. Primary Responsibilities - Analyze trading behaviors across various venues to discover execution issues and enhance latency and fill rates. - Develop Python libraries, data pipelines, and tools to manage exchange protocols, order flows, and extensive trading datasets. - Design analytical frameworks, metrics, and monitoring systems to assess execution quality and system performance. - Oversee live trading systems with a focus on data integrity, pipeline durability, and real-time monitoring. - Collaborate with stakeholders to translate analytical insights into tangible improvements in execution performance. - Work closely with research and infrastructure teams to advance execution analysis and market behavior insights continuously. Required Skills & Experience - Bachelor's or advanced degree in Computer Science, Engineering, Mathematics, or a related quantitative field. - Over 7 years of professional experience in Python development, including crafting libraries, data platforms, or analytical tools. - Expertise with large-scale and time series datasets utilizing tools like NumPy and Pandas. - In-depth SQL knowledge and experience with analytical databases. - Strong problem-solving skills for analyzing complex data and system behaviors. - Capability to translate analytical or trading-related challenges into reliable engineering solutions. - Experience working in Linux environments and applying best practices in software engineering such as testing, version control, and continuous integration. - Knowledge of financial markets, electronic trading, or execution analysis. - Experience with low-level programming languages such as C, C++, or Rust is advantageous. Compensation & Benefits - Competitive salary based on experience - Performance-based annual bonus - Outstanding compensation package Career Development & Growth - Clear pathways for advancement to Senior Developer and Tech Lead roles - Access to internal training resources and mentorship - Regular hackathons and allocated conference budget Ready to elevate your career? Join a team driven by innovation and collaboration. Apply today to be part of a forward-thinking company that values your expertise and supports your professional growth.

🏢 Summary: The offer is for an experienced Python Data Engineer to build scalable, cloud-based data and analytics solutions for global financial institutions. The role focuses on designing distributed data pipelines, enhancing system reliability, and developing financial and AI-driven data platforms. You will work with modern cloud and AI tools to advance enterprise data architecture and analytics capabilities. 🗂️ Requirements: 4+ years of professional experience in Python data or software engineering, Strong knowledge of data architecture, data modeling, and data warehousing, Advanced SQL skills and complex query writing, Experience building scalable distributed data pipelines, Hands-on experience with cloud environments (AWS preferred), Understanding of event-driven architectures, Experience with debugging and system reliability practices 📃 Skills: Python, SQL, AWS, Databricks, Spark, PySpark, Scala, Delta, Airflow, dbt, Kafka, Kubernetes, MongoDB, Grafana, Loki, Prometheus, OpenTelemetry 🏢 Description: We are partnering with top-tier global financial institutions to scale their core technology and data infrastructure. We are looking for an experienced and product-oriented Python Data Engineer to join our technology group. In this role, you will work at the intersection of cutting-edge technology and institutional finance. You will collaborate closely with data consumers, engineering teams, and business stakeholders to push the firm's technological capabilities forward. What You’ll Do: Core Responsibilities: Design, develop, and deliver high-quality, scalable Python-based solutions. Drive engineering excellence by ensuring system reliability, automating processes, and maintaining high operational standards. Actively experiment with and integrate modern AI coding tools (e.g., Copilot, Cursor) to streamline engineering workflows. Lead design discussions, mentor junior colleagues, and communicate proactively across a geo-distributed team. Depending on the specific project or team, your focus may include: Enterprise Data Platforms: Building cloud-based (AWS) pipelines for data ingestion, streaming, and cataloging. Risk & Portfolio Analytics Systems: Developing software for financial data ingress/egress, performance/exposure monitoring, and automated reconciliation. AI & Metadata Applications: Extending AI-powered semantic data access layers and internal data catalogs. What We’re Looking For Experience: 4+ years of professional experience in software or data engineering, specifically using Python . Data Skills: Solid understanding of data architecture, modeling, and warehousing. Excellent debugging acumen and comfort writing complex SQL statements. Cloud & Architecture: Experience building scalable, distributed pipelines in a cloud environment (preferably AWS ). Familiarity with event-driven architectures. Mindset: Impact-oriented, proactive, self-starting learner who embraces engineering automation, navigates ambiguity well, and holds themselves to high ethical standards. Nice to Have: Big Data & Orchestration: Expertise in Databricks, Spark (PySpark/Scala), Delta Lake, and orchestration tools like Airflow, dbt, or Kafka. Infrastructure & Observability: Working knowledge of Kubernetes, MongoDB, and observability stacks (Grafana, Loki, Prometheus, OpenTelemetry). Offer: Competitive compensation (30k - 45k PLN) with flexible contracting options (B2B/UoP). Premium office location in the heart of Warsaw. Comprehensive private medical and dental care. Sports card and wellness benefits. Private life insurance

🏢 Summary: Opportunity for an experienced Python Data Engineer to build scalable data platforms and analytics systems for global financial institutions. The role focuses on designing cloud-based data pipelines, enhancing system reliability, and integrating modern AI tools into engineering workflows. You will collaborate across distributed teams to deliver high-quality solutions in enterprise data, risk analytics, and AI-driven metadata applications. 🗂️ Requirements: 4+ years of professional experience in software or data engineering using Python, Strong knowledge of data architecture, data modeling, and data warehousing, Ability to write complex SQL queries and perform advanced debugging, Experience building scalable, distributed data pipelines in cloud environments, Experience with AWS, Familiarity with event-driven architectures 📃 Skills: Python, SQL, AWS, Databricks, Spark, PySpark, Scala, Delta, Airflow, dbt, Kafka, Kubernetes, MongoDB, Grafana, Loki, Prometheus, OpenTelemetry 🏢 Description: We are partnering with top-tier global financial institutions to scale their core technology and data infrastructure. We are looking for an experienced and product-oriented Python Data Engineer to join our technology group. In this role, you will work at the intersection of cutting-edge technology and institutional finance. You will collaborate closely with data consumers, engineering teams, and business stakeholders to push the firm's technological capabilities forward. What You’ll Do: Core Responsibilities: Design, develop, and deliver high-quality, scalable Python-based solutions. Drive engineering excellence by ensuring system reliability, automating processes, and maintaining high operational standards. Actively experiment with and integrate modern AI coding tools (e.g., Copilot, Cursor) to streamline engineering workflows. Lead design discussions, mentor junior colleagues, and communicate proactively across a geo-distributed team. Depending on the specific project or team, your focus may include: Enterprise Data Platforms: Building cloud-based (AWS) pipelines for data ingestion, streaming, and cataloging. Risk & Portfolio Analytics Systems: Developing software for financial data ingress/egress, performance/exposure monitoring, and automated reconciliation. AI & Metadata Applications: Extending AI-powered semantic data access layers and internal data catalogs. What We’re Looking For: Experience: 4+ years of professional experience in software or data engineering, specifically using Python . Data Skills: Solid understanding of data architecture, modeling, and warehousing. Excellent debugging acumen and comfort writing complex SQL statements. Cloud & Architecture: Experience building scalable, distributed pipelines in a cloud environment (preferably AWS ). Familiarity with event-driven architectures. Mindset: Impact-oriented, proactive, self-starting learner who embraces engineering automation, navigates ambiguity well, and holds themselves to high ethical standards. Nice to Have: Big Data & Orchestration: Expertise in Databricks, Spark (PySpark/Scala), Delta Lake, and orchestration tools like Airflow, dbt, or Kafka. Infrastructure & Observability: Working knowledge of Kubernetes, MongoDB, and observability stacks (Grafana, Loki, Prometheus, OpenTelemetry). Offer: Competitive compensation (30k - 45k PLN) with flexible contracting options (B2B/UoP). Premium office location in the heart of Warsaw. Comprehensive private medical and dental care. Sports card and wellness benefits. Private life insurance

🏢 Summary: Contract role focused on building and productionising Python-based data and ML systems that support front-office portfolio management and analytics. Involves designing scalable data pipelines, modernising legacy workflows, and delivering reliable solutions integrated with enterprise data platforms. High-impact position working closely with investment teams to enable proprietary models and core analytics. 🗂️ Requirements: Strong professional experience with Python engineering, Experience building ETL or ML-oriented Python workflows, Experience developing robust data pipelines, Experience working with parquet or columnar data formats, Experience with PySpark or distributed data processing, Experience working in Databricks or similar platform environments, Proficiency with Git, Experience with testing and code reviews, Experience with CI/CD pipelines, Understanding of software engineering best practices 📃 Skills: Python, ETL, ML, Parquet, PySpark, Spark, Databricks, Git, CI/CD, Testing, APIs, Containers 🏢 Description: Location: Flexible (Hybrid in Wroclaw) Department: Front‑Office Technology & Analytics Type: Contract About the Role We’re working with a leading global investment organisation that is expanding its front‑office engineering function. This role sits at the intersection of data engineering, applied data science, and front‑office portfolio support , with a focus on building high‑quality Python systems that directly enable portfolio managers, analysts, and risk teams. You’ll work across several investment teams, helping to rewrite key components, productionise POCs, optimise data access patterns, and deliver reliable, scalable pipelines that power core analytics and proprietary models. If you enjoy solving complex data problems, building production systems end‑to‑end, and working closely with front‑office stakeholders, this is a high‑impact opportunity. What You’ll Work On Design, build, and operate Python-based data pipelines (batch & near‑real‑time) reading/writing to governed enterprise storage (e.g., parquet patterns via internal cloud storage). Develop production‑ready ML/data components including feature prep, scoring pipelines, and API‑exposed data services. Support the re‑engineering and migration of legacy workflows into modern Python-based solutions. Partner directly with front‑office portfolio managers and analysts to extend and industrialise proprietary models. Optimise Databricks connectivity and collaborate with platform teams to improve Spark/PySpark workloads. Support portfolio teams with data access, connectivity principles, and technical design for productionisation. Contribute to engineering standards: CI/CD, testing, code reviews, observability, automation, and documentation. Work on POCs through to full production rollout, including rewriting logic from other languages into Python where required. What We’re Looking For Must‑Have Skills Strong, professional-level Python engineering skills (data structures, packaging, typing). Experience with ETL or ML‑oriented Python workflows. Experience building robust data pipelines and working with parquet/columnar formats in governed storage. Exposure to PySpark or distributed data processing . Comfortable working in platform environments (Databricks, containerised services, internal dev platforms). Strong software engineering foundations: Git, testing, code review, CI/CD , documentation.

🏢 Summary: Senior Python Engineer role focused on building and maintaining Python applications for AI and automation use cases in the financial domain. The position involves developing data pipelines, collaborating on machine learning model lifecycle, and delivering scalable solutions within a cross-functional team. Hybrid work model with office presence in Wroclaw three days per week. 🗂️ Requirements: Strong proficiency in Python, Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Keras, Scikit-learn), Solid understanding of linear algebra, probability, statistics, calculus, Practical experience with Pandas and NumPy, Knowledge of supervised, unsupervised, and reinforcement learning algorithms, Experience with debugging, testing, and Git-based version control 📃 Skills: Python, TensorFlow, PyTorch, Keras, Scikit-learn, Pandas, NumPy, Git, AI, ML, NLP, ComputerVision, C++, Java, R 🏢 Description: We are seeking a skilled Senior Python Engineer to join a Project for our Client, a global leader in the area of banking, investments and financial services. This position offers a hybrid model of work, with 3 days per week working from the office located in Wroclaw. Responsibilities Build and maintain Python applications supporting AI and automation use cases Develop data preprocessing, transformation, and feature engineering pipelines Collaborate on training, evaluating, and deploying machine learning models Implement best practices in testing, version control, and code quality Work within a cross-functional POD to deliver scalable, reliable solutions Requirements Strong proficiency in Python Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Keras, Scikit-learn) Solid understanding of linear algebra, probability, statistics, and calculus Practical experience with Pandas, NumPy, and data manipulation workflows Familiarity with ML algorithms (supervised, unsupervised, reinforcement learning) Exposure to deep learning, NLP, or computer vision is beneficial Strong debugging, testing, and Git-based version control skills Nice to have C++, Java or R Language experience We offer/Benefits We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

🏢 Summary: Senior Python Software Engineer role focused on building and operating production-grade Python applications and data pipelines, transforming data science prototypes into scalable, deployable services. The position emphasizes strong SDLC practices, API development, governed data environments and collaboration with platform teams using Databricks and Spark. It combines backend engineering, data processing and model service exposure in enterprise production environments. 🗂️ Requirements: 3+ years of Python engineering experience, Proficiency in Python packaging (wheels, pyproject), Experience with typing, clean architecture and error handling, Strong production SDLC experience (Git workflows, automated tests, CI/CD, code reviews), Strong skills in Pandas and NumPy, Experience with Parquet and governed data access patterns, Experience building APIs with FastAPI, Flask or similar frameworks, Experience working in Databricks or other governed platform environments 📃 Skills: Python, Pandas, NumPy, Parquet, FastAPI, Flask, Databricks, Spark, PySpark, Git, CI/CD, scikit-learn 🏢 Description: We are seeking a Senior Python Software Engineer (Production Data & Model Services) to design, build and operate production-grade Python applications and data pipelines. In this role, you will transform quantitative and data science prototypes into robust, deployable services while collaborating closely with platform teams to ensure scalable and well-governed solutions. Responsibilities Build and run production-grade Python applications including APIs and batch jobs with strong SDLC practices covering code reviews, testing, CI/CD, observability and documentation Develop robust batch and near-real-time data pipelines reading and writing governed storage with Parquet and columnar formats following approved patterns Transform quant and data science prototypes into deployable packages and services that are typed, modular and versioned Expose scoring and analytics capabilities via APIs or scheduled jobs rather than notebook-only deliverables Collaborate with platform teams on Databricks and Spark connectivity Optimize PySpark workloads when needed to ensure performance and scalability Maintain release discipline through Git workflows, automated tests and code reviews Operate within governed platform environments to ensure compliance and reliability Requirements 3+ years of experience in Python engineering with proficiency in packaging (wheels/pyproject), typing, clean architecture, error handling and performance mindset Proven background in production SDLC including Git workflows, automated tests, CI/CD, code reviews and release discipline Strong skills in Pandas and NumPy applied to production pipelines Familiarity with data formats such as Parquet and governed data access patterns Experience building and operating APIs and services using FastAPI, Flask or similar frameworks Competency in working within governed platform environments such as Databricks or containerized dev platforms Nice to have Skills in scikit-learn for production feature and scoring pipelines, including reproducible transforms and model packaging/versioning Background in PySpark and distributed processing Familiarity with IDE-to-Databricks workflows such as Databricks Connect We offer We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

🏢 Summary: Hands-on Quantitative Software Engineer role focused on building and optimizing a high-performance research-to-trading platform for quantitative investment strategies. The position involves developing analytics, pricing libraries, and production trading systems using C++ and Python, with direct collaboration with researchers and investment professionals. Emphasis is placed on scalable data pipelines, performance tuning, and reliable production infrastructure. 🗂️ Requirements: Degree in Computer Science, Engineering, Mathematics, Physics, or related quantitative field, 3+ years of software engineering experience in production environments, Strong programming skills in Python, Strong programming skills in modern C++, Experience with SQL and relational databases, Experience with Linux development, Experience building, deploying, and supporting production systems, Strong performance tuning, debugging, and optimization skills, Understanding of financial markets (equities, futures, FX) and market data usage, Strong analytical and problem-solving skills 📃 Skills: Python, C++, SQL, Linux, CMake, Git 🏢 Description: Quantitative Software Engineer Warsaw, hybrid. Join a team building a research-to-trading platform used to design, test, and deploy quantitative investment strategies. This is a hands-on engineering role focused on high-performance analytics, market data, and production trading infrastructure . Responsibilities Develop and maintain C++ and Python applications supporting quantitative research and trading. Build analytics, pricing libraries, and tools for backtesting, simulation, and production trading. Design and optimize data pipelines handling large historical and real-time market datasets. Develop and support production services, including testing, deployment, and monitoring. Improve platform scalability, reliability, and performance. Partner directly with researchers and investment professionals to deliver robust, production-grade solutions. Contribute to technical roadmap, automation, and engineering best practices. Requirements Degree in Computer Science, Engineering, Mathematics, Physics, or a related quantitative field. 3+ years of software engineering experience in production environments. Strong programming skills in Python and modern C++ . Experience with SQL, relational databases, and Linux development . Experience building, deploying, and supporting production systems. Strong performance tuning, debugging, and optimization skills. Understanding of financial markets (equities, futures, FX) and market data usage. Strong analytical, problem-solving, and communication skills. Nice to Have Experience working directly with quantitative research or trading teams. Background in low-latency or high-throughput systems. Experience with large-scale data processing and analytics platforms.