Senior Data Engineer

You’ll Get To

This role supports an AI-powered Invoice-to-Cash (I2C) solution that uses intelligent automation to help companies collect cash faster, unlock working capital, and improve accounts-receivable efficiency.

Make Your Mark

As a Senior Data Engineer on the Business Intelligence & Analytics Engineering team in Krakow, you will be a hands-on builder of the data platform behind a mission-critical, AI-powered SaaS product. You will design and deliver pipelines, models, and reports that customers and internal teams use to make high-impact decisions.

You will build data flows from transactional systems into Snowflake, model data for reliability and performance, and surface trusted, actionable insights through Power BI. Working with Staff Engineers, the Manager, and Product partners, you will own well-scoped platform areas, raise engineering quality, and grow toward technical leadership. You will use AI development tools such as Claude and Cursor to accelerate delivery and improve quality across the data platform.

Benefits

• Retirement: PPK
• Life & Disability: Unum
• Healthcare: Luxmed Poland
• Wellness benefit: Multisport
• Business travel accident insurance: AIG coverage for business-travel medical expenses, life, and accidental injury
• Employee assistance program: Telus Health
• Annual performance bonus: 7–15%, depending on level and performance
• Restricted Stock Units (RSUs) for eligible employees
• Reduced tax-deductible expenses; 84% of programmers’ time is recognized as creative work

You’ll Get To

• Build and govern data pipelines: Design, implement, and maintain robust ELT/ETL pipelines that reliably move and transform data from operational systems, including microservices, event streams, and third-party sources, into well-modelled, analytics-ready datasets in Snowflake.
• Deliver trusted analytics with Power BI: Develop enterprise-grade Power BI reports and dashboards for internal stakeholders and customer-facing analytics; build semantic models, row-level security, and a governed BI layer.
• Contribute to data platform architecture: Help shape and evolve end-to-end Snowflake data architecture, from ingestion and transformation to serving, while maintaining scalability, cost efficiency, and reliability.
• Champion modern data modelling: Apply transformation practices to produce modular, well-tested, and documented data models.
• Champion AI-accelerated development: Use and promote agentic development tools, such as Cursor and Claude, for pipeline development, query optimization, and documentation.
• Build in data quality and observability: Incorporate data-quality frameworks, automated testing, and monitoring into pipelines to identify issues before they affect customers or business decisions.
• Grow and share your craft: Improve team practices through code reviews, documentation, and knowledge sharing on data modelling, Snowflake optimization, and BI best practices.
• Collaborate across the organization: Partner with Software Engineers, Product Managers, and Finance stakeholders to translate data needs into reliable data products and communicate platform capabilities and constraints.

Technical / Specialized Knowledge, Skills, and Abilities

• Strong hands-on Snowflake experience, including data modelling, performance tuning, cost optimization, clustering or dynamic tables, and Snowflake-native security and governance features.
• Solid Power BI proficiency, including semantic models, DAX, Power Query, enterprise report design, row-level security, incremental refresh, and the Power BI service.
• Proven experience building and operating production ELT/ETL pipelines with dbt, Apache Airflow, Azure Data Factory, or equivalent orchestration frameworks.
• Expert-level SQL and working knowledge of at least one general-purpose language; Python is preferred for data processing and automation.
• Demonstrated use of AI-driven development tools, such as Cursor and Claude, to improve data-engineering velocity and quality.
• A strong data-quality and observability mindset, including monitoring, alerting, and testing built into pipelines from the start.
• Ability to independently own well-scoped initiatives, from ambiguous requirements through reliable, well-adopted data products.
• Excellent written and verbal communication skills, including the ability to translate technical data concepts into business requirements and collaborate across time zones.

We’re Even More Excited If You Have

• Experience in a regulated industry, such as finance, accounting, or fintech, with awareness of data governance, auditability, and compliance requirements.
• Familiarity with Microsoft Fabric, including database mirroring from Azure-hosted sources into an analytical data platform.
• Familiarity with cloud-native data architectures on Azure or AWS, particularly Azure Synapse, Azure Data Lake, AWS Glue, or S3-based data lake patterns.
• Experience with streaming or event-driven ingestion using Kafka, Azure Event Hubs, or similar tools for near-real-time analytical workloads.
• Knowledge of Responsible AI principles and experience building data infrastructure for trustworthy, auditable AI/ML pipelines.
• Contributions to open-source data tooling or interest in emerging modern data-stack patterns.

Workplace

Candidates who live within a reasonable commute of an office will work in the office at least 3 days a week.