[Blackline] Staff Data Engineer

BlackLine is a leading provider of cloud software that automates and controls the entire financial close process. The company focuses on modernizing finance and accounting functions, delivering innovative SaaS solutions such as an AI-powered Invoice-to-Cash platform. The role is based in Krakow, Poland, in a new Engineering Hub dedicated to this AI-powered SaaS product.

• Proven expertise using AI-driven development tools such as Cursor and Claude to enhance data engineering velocity and quality.
• Deep knowledge of Snowflake including data modelling, performance tuning, cost optimization, clustering, dynamic tables, and security.
• Advanced proficiency in Power BI with experience in semantic models (DAX, Power Query), report design, row-level security, incremental refresh, deployment pipelines, and service administration.
• Strong experience with ELT/ETL orchestration tools such as dbt, Apache Airflow, or Azure Data Factory.
• Expert-level SQL skills and working knowledge of at least one general-purpose language, preferably Python, for data processing and automation.
• Demonstrated technical leadership driving complex cross-functional data initiatives.
• Strong data quality and observability mindset with monitoring and automated testing integration.
• Excellent written and verbal communication skills for technical and business translation across time zones.

Nice to have:

• Experience in regulated industries like finance or fintech with data governance and compliance.
• Familiarity with cloud-native architectures on Azure or AWS, including Azure Synapse, Azure Data Lake, AWS Glue, or S3 data lakes.
• Experience with streaming or event-driven ingestion using Kafka or Azure Event Hubs.
• Knowledge of Responsible AI principles and building trustworthy AI/ML pipelines.
• Contributions to open-source data tooling or interest in emerging modern data stack patterns.
• Experience building data practices from scratch, including data cataloguing, lineage, and self-serve BI.

• Architect and own the end-to-end data platform on Snowflake, ensuring scalability and performance.
• Build and maintain ELT/ETL data pipelines for ingestion and transformation from various operational systems.
• Lead development of enterprise Power BI reports and dashboards with semantic models and row-level security.
• Promote modern data modelling practices with modular, documented, and tested data models.
• Utilize AI-driven development tools like Cursor and Claude to accelerate pipeline development and documentation.
• Implement data quality frameworks, automated testing, and monitoring across the data platform.
• Mentor and lead data engineers, conduct code reviews, and share best practices.
• Collaborate with software engineers, product managers, and finance stakeholders to meet data needs.