Senior Data & AI Platform Engineer

New

H2B GroupData platforms

Workplace type: remote; Locations: Gdańsk, Abrahama 1a, Gdańsk, Country code: PLContractSenior

Salary130 - 190 PLN per hour

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Job Details

Languages: En C1
Experience: Minimum 6 years of experience in data engineering, data platforms, or analytics engineering.
Required Skills: PythonSQLMicrosoft Power BIDatabricksPySpark

Have at least 6 years of experience in data engineering, data platforms, or analytics engineering.
Have practical proficiency in Microsoft Fabric, or strong Azure Synapse/Databricks experience and readiness to work with Fabric immediately.
Have advanced SQL/T-SQL skills.
Be proficient in Python or PySpark for building ETL/ELT pipelines and analytical data models.
Have strong Power BI and DAX skills, including semantic modeling, incremental refresh, query performance optimization, and capacity/cost awareness.
Have experience with legacy-to-modern migrations in data and reporting, including data consistency validation and change management.
Have experience operating production systems, including monitoring, root-cause analysis, data lineage, and data-quality rules.
Be proficient with Git, including pull requests and CI/CD for notebooks, pipelines, and models.
Have practical experience using AI or automation tools to support engineering development, testing, or documentation.
Financial, payment, SaaS, marketplace, fintech, e-commerce, or B2B2C experience is relevant; finance and payment domain knowledge is a plus.
Reverse-ETL, CRM, NoSQL-to-analytics modeling, product or marketing analytics sources, Azure OpenAI, LLM, RAG, Responsible AI, and sensitive-data governance are listed as nice-to-haves.

Design and implement Microsoft Fabric solutions using Lakehouse, Warehouse, Notebooks, and semantic models, with Git versioning and governance rules.
Migrate legacy metrics and reporting tools to the Fabric semantic layer, including metric parity testing, business validation, and retirement of old systems.
Design, optimize, and maintain data pipelines integrating APIs, files, events, and operational databases.
Implement orchestration, monitoring, alerts, and automated data-quality checks.
Use AI/LLM solutions to accelerate ETL/ELT, schema mapping, documentation, testing, and anomaly detection.
Build advanced Power BI semantic models, DAX calculations, and reusable business metric definitions.
Maintain CRM and operational data flows, map identities and schemas, and feed target systems through Reverse-ETL.
Create repeatable data ingestion and modeling patterns for acquired businesses, supporting reporting continuity and auditability.
Define Ready/Done criteria, code-review standards, release procedures, and technical runbooks; support other engineers and analysts.

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