Senior Data Engineer

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SeniorOn-site·KrakówFull-time

#425190·Dodano miesiąc temu·2

Źródło: IT MATCH

🚫Oferta wygasła. Ta oferta pracy nie jest już aktywna i rekrutacja została zakończona.

Tech Stack / Keywords

CloudAISnowflakePower BIETL MicroservicesSecurityArchitecture

Firma i stanowisko

BlackLine is a leading provider of cloud software automating financial close processes, committed to modernizing finance and accounting functions globally. The role is part of the Business Intelligence & Analytics Engineering team in Krakow, focused on the AI-powered Invoice-to-Cash (I2C) SaaS solution.

Wymagania

Strong hands-on experience with Snowflake, including data modelling, performance tuning, and security features.
Proficiency with Power BI: DAX, Power Query, semantic models, row-level security, incremental refresh.
Experience with production ELT/ETL pipelines using tools such as dbt, Apache Airflow, or Azure Data Factory.
Expert-level SQL and proficiency in at least one general-purpose language (preferably Python).
Experience using AI-driven development tools (e.g., Cursor, Claude).
Strong data quality and observability mindset integrating monitoring and testing.
Ability to work independently and take ownership of data products.
Excellent communication skills to bridge technical concepts and business requirements across time zones.

Nice to have:

Experience in regulated industries (finance, accounting, fintech) with focus on data governance and compliance.
Familiarity with Microsoft Fabric and Azure/AWS cloud data architectures (Azure Synapse, AWS Glue).
Experience with streaming data ingestion using Kafka, Azure Event Hubs, or similar.
Knowledge of Responsible AI principles and building trustworthy AI/ML pipelines.
Contributions to open-source data tooling or interest in modern data stack patterns.

Obowiązki

Design, implement, and maintain ELT/ETL data pipelines from operational systems into Snowflake.
Develop enterprise-grade Power BI reports and dashboards with semantic models and row-level security.
Shape and evolve end-to-end data architecture on Snowflake ensuring scalability and cost efficiency.
Apply best practices in data modelling producing modular, well-tested data models.
Use AI development tools like Cursor and Claude to accelerate development and optimize queries.
Implement data quality frameworks, automated testing, and monitoring in pipelines.
Conduct code reviews, documentation, and knowledge sharing on data modelling and BI best practices.
Collaborate with Software Engineers, Product Managers, and Finance stakeholders to meet data needs.

IT MATCH

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