Data Engineer, TS/SCI

🏢 Summary: Full-time Data Engineer role focused on leading the data lifecycle strategy, transforming and governing large-scale datasets, and integrating advanced analytics and machine learning models into a production data infrastructure. The position involves building high-quality, traceable data architectures and enabling real-time, data-driven decisions for government-related markets. Based in Pittsburgh, PA, with limited travel requirements. 🗂️ Requirements: U.S. Citizenship, Bachelor’s degree in Computer Science, Mathematics, or related technical field, 3–5 years of experience programmatically transforming data, Experience with RDBMS, Advanced SQL programming skills, Proficiency with CSV, XML, and JSON data formats, Strong analytical skills and attention to detail, Ability to work independently with minimal supervision 📃 Skills: SQL, RDBMS, CSV, XML, JSON, AWS, DataModeling, DataGovernance, ETL, MachineLearning 🏢 Description: Company Description Air is the leader in Enterprise Readiness. Our mission is to establish readiness as a real-time condition that is continuously achieved. Today, a dangerous Readiness Gap exists between what the front line needs and what is delivered. Our AI-native platform, Air Enterprise Readiness, aligns development, production, delivery, and sustainment into one coordinated execution system for government agencies and industrial suppliers. By revealing true capacity, exposing real constraints, coordinating resources, and executing at the speed of operational demands, the front line gets what it needs to succeed. Job Description We are seeking an exceptional and experienced data engineer who shares our passion and obsession with quality. You'll be a core member of our product and engineering team dedicated to helping our clients replace time-consuming, manual processes to reach informed real-time decisions about government markets, competitors, and agency relationships. We need a skilled and dedicated data engineer to join our team to lead us in uncovering truth and meaning in data. You must be a hands-on engineer with a strong understanding of both data management and governance standards. You must also have strong interpersonal skills to work cross-functionally across internal teams as well as directly with end users and platform SMEs. This role is a full-time position located out of our office in Pittsburgh, PA. This role may require up to 10% travel. Scope of Responsibilities Define and lead the data lifecycle strategy across data acquisition, data ingestion, data cleansing, normalization and linkage. Ensure key entities within datasets are identified, resolved and linked to existing entities within the current master data repository. Apply various techniques to produce solutions to large-scale optimization problems, including data pre-processing, indexing, blocking, field and record comparison and classification. Improve data sharing, increase data repurposing and improve cost efficiency associated with data management efforts. Build best practices that help with chain of custody of data so it can be easily traced back to the source for accuracy and consistency. Work across functional teams to understand advanced statistical, machine learning, and text processing models and incorporate them into the existing data engineering infrastructure. Perform exploratory data analyses, generate and test working hypotheses, prepare and analyze historical data and identify patterns. Work directly with users as well as SMEs to establish, create and populate optimal data architectures and structures, as well as articulate techniques and results using non-technical language. Qualifications U.S. Citizenship is required. Bachelor's degree in Computer Science, Mathematics or a related technical field. Required Skills: 3-5 years experience with programmatically transforming data. Experience with RDBMS. Advanced SQL programming skills. Proficient usage of common data formats such as CSV, XML, and JSON. Strong analytical ability and attention to detail. Ability to work independently with little supervision. Desired Skills: Current possession of a U.S. security clearance, or the ability to obtain one with sponsorship. Experience using Amazon Web Services. Working knowledge with large (multiple terabytes) amounts of data. Air is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans status or any other characteristic protected by law.

🏢 Summary: The offer is for a Data Engineer/DevOps professional to build and maintain scalable data platforms and cloud infrastructure, automate data workflows using CI/CD and Infrastructure as Code, and optimize data pipelines for high availability and security. The role focuses on managing data processing environments and supporting model deployment in collaboration with data teams. 🗂️ Requirements: Proficiency in Linux/Unix administration, Strong Shell scripting skills, Advanced knowledge of Python, Advanced knowledge of SQL, 3–5 years experience in Data Engineering or DevOps, Degree in Computer Science, Data Engineering, or related field 📃 Skills: Linux, Unix, Shell, Python, SQL, Azure, Spark, Databricks, Docker, Kubernetes, Terraform, Ansible, Hadoop, Kafka, CICD 🏢 Description: Key Responsibilities Infrastructure Management: Build and maintain scalable data platforms and cloud-based infrastructure. Automation: Implement CI/CD pipelines for data workflows and automate manual processes using Infrastructure as Code (IaC). Pipeline Optimization: Monitor, troubleshoot, and optimize data processing jobs to ensure high availability. Security & Compliance: Ensure data integrity and security across all environments. Collaboration: Work closely with Data Scientists and Engineers to streamline the deployment of data models. Requirements Systems & Scripting: Strong proficiency in Linux/Unix administration and Shell scripting. Programming: Advanced knowledge of Python and SQL . Mindset: Exceptional analytical and problem-solving skills. Education: Degree in Computer Science, Data Engineering, or a related technical field. Experience: 3–5 years of proven experience in Data Engineering or a DevOps-related role. Nice-to-have Cloud & Big Data: Hands-on experience with Azure , Apache Spark , and Databricks . DevOps Tools: Proficiency with Docker , Kubernetes , CI/CD tools, and IaC (e.g., Terraform, Ansible). Data Ecosystems: Familiarity with Big Data technologies such as Hadoop or Kafka .

🏢 Summary: Senior backend engineering role focused on designing and operating large-scale batch and streaming data pipeline platforms with strong reliability and performance requirements. The position involves building distributed systems, pipeline orchestration services, and cloud-native platform capabilities using Java and modern data technologies. The role also includes technical leadership, CI/CD improvements, and collaboration across international engineering teams. 🗂️ Requirements: Strong backend engineering experience with Java, Experience building production-grade distributed systems, Expertise in software architecture and system design, Experience with high-throughput and low-latency systems, Knowledge of REST APIs and microservices, Hands-on experience with AWS and cloud-native design, Experience with Docker and Kubernetes, Experience with Flink, Spark, or Kafka, Familiarity with CI/CD pipelines and DevOps practices, Experience with Jenkins, GitLab, Git, and JIRA, Strong communication skills 📃 Skills: Java, Flink, Spark, Kafka, AWS, EMR, S3, REST, Microservices, Docker, Kubernetes, Jenkins, GitLab, Git, JIRA, HTTP 🏢 Description: The Pipeline Management team builds and operates a core platform that powers large-scale batch and streaming data pipelines across HERE’s Data Platform. Our platform enables internal teams and customers to design, deploy, and operate data pipelines at scale, supporting mission-critical workloads with strong reliability and performance requirements. Lead the design and development of pipeline management services and APIs Own and evolve key platform components, including pipeline orchestration, scheduling, and workflow state management Drive architecture for high-throughput, low-latency distributed systems Partner with Product and engineering teams to deliver scalable data platform capabilities Mentor engineers and provide technical leadership across a distributed team Improve system reliability, observability, and SLA adherence for production services Contribute to CI/CD, automation, and engineering best practices across the platform Technology Stack: You will work with a modern data platform ecosystem including: Data Processing: Apache Flink, Apache Spark Backend & Services: Java (primary), REST APIs, microservices Streaming & Messaging: Apache Kafka Cloud & Infrastructure: AWS (EMR, S3) Platform Services: Pipeline Service, Scheduler, State Service, Coordinator CI/CD & Tooling: Jenkins, GitLab pipelines, Git, JIRA Who are you? Strong backend engineering experience with Java (preferred), building production-grade distributed systems Expertise in software architecture and system design Experience building and operating high-throughput, low-latency, highly reliable distributed systems Solid understanding of REST APIs, HTTP, and microservices architectures Hands-on experience with cloud platforms (AWS preferred) and cloud-native design Experience with containerization and orchestration (Docker, Kubernetes) Experience with data processing and streaming systems (e.g., Flink, Spark, Kafka) Strong familiarity with CI/CD pipelines and engineering tools (e.g., Jenkins, GitLab, Git, JIRA) Experience applying DevOps practices to improve system reliability and delivery velocity Strong communication skills with the ability to clearly explain complex concepts Nice to Have Experience with pipeline orchestration platforms or workflow engines Exposure to large-scale data platforms or multi-tenant systems Experience with cloud platform migrations or modernization initiatives What we offer: Work on on globally deployed automotive navigation and mapping products Collaboration with an experienced, international engineering organization Truly international team of fantastic & talented people from 60+ countries worldwide, working from strong tech hubs located in Europe, the US, and Asia, along with multiple smaller locations Flexible working hours & a flexible approach to office vs. remote work Medical coverage for you and your family Yearly variable bonus This role is eligible for the Creative Tax Incentive scheme in Poland (KUP) Option to work on a B2B contract (please note: benefits, bonus and KUP do not apply in this case)

🏢 Summary: DevOps Engineer role focused on supporting and scaling modern data platforms by combining DevOps practices with data engineering expertise. The position involves building and maintaining CI/CD pipelines, managing cloud-based data infrastructure, and ensuring reliable, automated data workflows. You will collaborate with data teams to optimize performance, scalability, and security of data solutions. 🗂️ Requirements: 4–5 years experience in DevOps or similar role, Hands-on experience with Databricks, Strong experience with AWS, Experience building and maintaining CI/CD pipelines with Jenkins, Background in data engineering or data platforms, Basic to intermediate Python knowledge, Understanding of ETL/ELT processes, Knowledge of distributed data systems 📃 Skills: Jenkins, Databricks, AWS, Python, CICD, ETL, ELT, DevOps, DataEngineering, Cloud, DistributedSystems 🏢 Description: About the Role We are looking for a DevOps Engineer with a strong data background to support and scale modern data platforms. In this role, you will work at the intersection of DevOps and Data Engineering , ensuring reliable, automated, and efficient data pipelines and environments. You will be responsible for maintaining and improving CI/CD processes, supporting cloud-based data platforms, and collaborating with data engineers and analytics teams to enable smooth data operations. Key Responsibilities Design, implement, and maintain CI/CD pipelines using Jenkins . Manage and optimize data platforms based on Databricks . Build and maintain cloud infrastructure on Amazon Web Services . Support deployment, monitoring, and troubleshooting of data pipelines and workflows. Collaborate closely with data engineers to improve reliability and performance of data solutions. Automate infrastructure and operational processes. Ensure best practices in security, scalability, and performance across the platform. Required Skills & Experience 4–5 years of experience in a DevOps Engineer or similar role. Hands-on experience with Databricks . Strong experience with Amazon Web Services . Experience building and maintaining CI/CD pipelines using Jenkins . Background in data engineering or experience working with data platforms. Basic to intermediate knowledge of Python . Understanding of data pipelines, ETL/ELT processes, and distributed data systems. Strong problem-solving skills and ability to troubleshoot complex issues. Good communication skills and ability to work in cross-functional teams.

🏢 Summary: Hands-on data infrastructure engineering role focused on large-scale pipeline migrations and evolution of the company’s data processing stack. The position involves contributing to platform development across Flink and Lakehouse architectures while ensuring performance, reliability, and cost efficiency. High-impact role embedded in a data engineering team delivering production-grade data platforms. 🗂️ Requirements: Strong Java development experience, Experience with JVM-based data processing framework, Experience with Flink, Beam, Dataflow or Spark, Proficiency in SQL, Experience with BigQuery, Experience with cloud infrastructure, Experience with containerized applications, Knowledge of Kubernetes basics, Experience with Scala or Python for data pipelines, Experience working with production data engineering systems 📃 Skills: Java, Flink, Beam, Dataflow, Spark, SQL, BigQuery, Kubernetes, Scala, Python, JVM, DevOps, Lakehouse, Cloud 🏢 Description: The Data Infrastructure PA enables the company to solve complex and critical data engineering problems by providing platforms and tooling for the production, management, and consumption of high-quality data. We're looking for an engineer to support hands-on implementation and migration work as we evolve our data processing stack. This is a high impact and execution-focused engagement — you'll be contributing to company wide migration efforts and platform development. What You'll Work On You'll be embedded in a team in Data Infrastructure PA, contributing to hands-on engineering work. This includes large-scale pipeline migrations — validating performance and cost outcomes and helping move workloads to our evolving stack — as well as contributing to platform development across our Flink platform, Lakehouse architecture and beyond, as our priorities evolve. What We're Looking For You have solid, hands-on experience in backend engineering and are comfortable jumping into an existing platform codebase and making meaningful contributions quickly. Specifically: Strong Java development skills, with experience in data platform or data engineering contexts Practical experience with at least one JVM-based data processing framework — Flink experience is a plus; Beam, Dataflow, or Spark also relevant Comfortable with SQL and cloud data analytics platforms, particularly BigQuery DevOps is part of your day-to-day: you work with cloud infrastructure, containerised applications, and are familiar with Kubernetes basics Experience working with data engineering pipelines in Scala and/or Python You write quality code and understand what it means to ship reliably in a production environment You can work autonomously in an ambiguous environment and move quickly without waiting to be directed Nice to Have Prior experience with large-scale pipeline migrations Familiarity with cost optimisation in cloud data processing workloads Job Posting Start Date:   2026-05-18 Job Posting End Date:   2026-11-27

🏢 Summary: Senior Technical Expert role focused on evolving a Data Marketplace built on Data Mesh principles from a modular monolith to a microservices architecture. The position involves hands-on development in Java 21, integration of AI-driven search capabilities, and design of scalable AWS infrastructure. The goal is to deliver a seamless, e-commerce-like experience for accessing and managing digital data assets. 🗂️ Requirements: Strong experience with Java 21+, Experience with Spring Boot 3.x, Hands-on experience with messaging technologies (Solace preferred), Experience with Angular and TypeScript in SPA architecture, Knowledge of microservices and modular monolith architecture, Understanding of Data Mesh and Domain-Driven Design, Experience with PostgreSQL and MongoDB, Experience with search platforms (e.g. Sinequa), Practical experience with AWS (EC2, RDS, Lambda, EKS), Experience with Infrastructure as Code (Terraform), Knowledge of integration patterns and enterprise networking 📃 Skills: Java, Spring, Solace, Angular, TypeScript, PostgreSQL, MongoDB, Sinequa, AWS, EC2, RDS, Lambda, EKS, Terraform, Microservices, DataMesh, DDD, CI/CD 🏢 Description: As a Senior Technical Expert, you will be the technical cornerstone of our Data Marketplace —a platform built on Data Mesh principles. You will guide the evolution of a "shop-for-data" experience, moving our architecture from a robust Modular Monolith to a distributed Microservices ecosystem. You’ll be working with a cutting-edge stack (Java 21, AWS, AI-enhanced search) to ensure that "buying" digital assets is as seamless for our users as a consumer e-commerce experience. The end-goal is to build a comprehensive solution that enables FAIR data access to Digital Assets across the organization. Key Responsibilities Architectural Evolution: Lead the strategic transition from a modular monolith to microservices, ensuring domain boundaries are respected and performance remains high. Take ownership of the development of new components and ideas as you cooperate with a multidisciplinary team to deliver end-to-end experiences to the End Users. Lead Development: Write clean, high-performance code using Java 21+ features (Virtual Threads, Pattern Matching) to handle complex data transactions. Search & AI Innovation: Work on the roadmap to integrate AI/LLM capabilities into our search engine ( Sinequa ), enabling users to explore data assets via natural language and intelligent discovery. Data Stewardship: Oversee the polyglot persistence layer, optimizing PostgreSQL for relational integrity and MongoDB for flexible metadata storage. Cloud Leadership: Design and maintain scalable infrastructure within AWS , ensuring our CI/CD pipelines and deployment strategies are best-in-class. Mentorship: Act as a force-multiplier for the team, conducting rigorous code reviews and setting the standard for technical excellence. Requirements Technical Requirements Strong experience with modern Java (21+) and Spring Boot 3.x Hands-on experience with messaging technologies, ideally Solace Good understanding of SPA architecture and frontend development with Angular and TypeScript Familiarity with integration patterns and enterprise networking Solid architectural knowledge, including modular monoliths, microservices, Data Mesh, and Domain-Driven Design Experience working with PostgreSQL, MongoDB, and search platforms such as Sinequa Practical experience with AWS services, including EC2, RDS, Lambda, and EKS Experience with Infrastructure as Code, preferably Terraform Who You Are A Technical Visionary: You don't just solve today's bugs; you anticipate where the architecture will break two years from now. Data-Centric: You understand that in a Data Mesh, the product is the data itself. You care about metadata, lineage, and discoverability. User-Centered: You care about the end users experience and can cooperate with UX and Frontend developers to map and deliver first-in-class solutions. Pragmatic Architect: You know when to stick with a monolith for speed and exactly when the "swell" justifies a move to microservices. AI Curious: You are excited about moving beyond keyword search into the realm of semantic search and AI-driven data exploration. The Roadmap: What You’ll Build Phase 1: Refine the modular boundaries of the current Java 21 application. Deliver scalable and extensible transaction modules enabling Request-to-Use processes within the DataMarketPlace Phase 2: Orchestrate the "Great Migration"—consolidate existing Marketplace ecosystems into DataMarketPlace on-boarding tens of thousands of assets and thousands of users. Phase 3: Integrate AI-driven exploration features atop our Sinequa search layer. Salary: 22 000 - 33000 PLN + VAT (B2B)

🏢 Summary: Senior Data Engineer role focused on designing and building scalable serverless data ingestion pipelines in AWS within the healthcare domain. The position emphasizes strong Python engineering, cloud architecture leadership, and implementation of modern data platforms and DevOps practices. The role involves driving technical excellence and delivering reliable, high-impact data solutions in an international environment. 🗂️ Requirements: 10+ years of experience in Python programming, Strong software engineering skills in data processing, Extensive experience with AWS Cloud and Serverless Architecture, Hands-on experience with AWS Lambda, S3, and Cognito, Experience building E2E automated tests for data pipelines, Practical knowledge of Data Mesh and Medallion Architecture, Experience with Infrastructure as Code using AWS CDK or Terraform, Experience with CI/CD pipelines using GitLab or GitHub Actions, Experience with ETL/ELT processes and dbt, Experience working with GraphQL, Minimum B2 level English proficiency 📃 Skills: Python, AWS, Lambda, S3, Cognito, Boto3, DataMesh, Medallion, CDK, Terraform, GitLab, GitHubActions, ETL, ELT, dbt, GraphQL, CI/CD 🏢 Description: We are looking for a highly skilled Data Engineer to join our client in the healthcare sector. Our requirements: Technical Expertise: Python Programming: 10+ years of experience with strong Software Engineering skills focused on data processing. AWS & Serverless: Extensive experience with AWS Cloud, specifically focusing on Serverless Architecture and services (including AWS Lambda , AWS S3 Tables , and AWS Cognito ). Automated Testing: Proven experience in developing End-to-End (E2E) automated tests to ensure pipeline reliability, utilizing tools such as Boto3 for AWS resource validation. Data Concepts: Practical knowledge of Data Mesh and Medallion Architecture , along with general data processing and analysis. DevOps & IaC: Hands-on experience with Infrastructure as Code ( AWS CDK or Terraform ) and CI/CD pipelines ( GitLab pipelines or GitHub Actions ). Modern Tooling: Experience with ETL/ELT solutions, dbt , and GraphQL . Communication & Soft Skills: English Language: Minimum B2 level , enabling smooth daily technical and business communication in a global environment. Collaboration: Excellent communication skills and the ability to thrive in a collaborative, international team. Standards: A strong commitment to high standards of ethics, quality (Clean Code), and reliable delivery. Nice to have: Experience with Snowflake and SQL . Knowledge of Data Vault 2.0 modeling. Experience with Databricks . Familiarity with the Microsoft ecosystem: C# / .Net, T-SQL, SQL Server , and Azure DevOps . Experience with Star Schema database modeling. Knowledge of Descriptive Statistics. Your responsibilites: Design and build scalable Data Ingestion pipelines within the AWS cloud ecosystem. Lead technical delivery and implementation of core platform components, ensuring architectural integrity across the entire data lifecycle. Collaborate with Engineering Managers and cross-functional teams across the globe and Poland. Drive technical excellence by improving team processes, architecture standards, and engineering best practices. Support and consult with stakeholders to ensure successful delivery of high-impact, data-driven solutions. Contribute to the growth and maturity of the team’s cloud and data engineering capabilities. We offer: Challenging role within the company that creates innovative solutions. Work in international environment on demanding projects. Remote work model. Subsidized private medical care, life insurance, multisport card. Integration meetings. Employee referral program. If you have a deep expertise in Python and AWS , and building scalable Serverless data architectures is where you truly excel, this is the perfect role for you!