Data Engineer

The Role

• Design and implement scalable ETL/ELT pipelines in a lakehouse architecture using Databricks, Azure Data Factory, and Azure Data Lake.
• Create analytical data models and structures optimized for performance and usability.
• Drive best practices in data engineering, including CI/CD with Azure DevOps, Git workflows, testing, and monitoring.
• Integrate workflows and orchestration using Airflow and other tools.
• Troubleshoot, monitor, and improve data quality, pipeline reliability, and job performance across distributed systems.
• Work with stakeholders to understand data requirements and deliver scalable, maintainable solutions.

What You'll Need

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in data engineering, with a focus on cloud-native platforms.
• Hands-on expertise with Azure Data Factory, Databricks, Azure Data Lake, SQL, and Python.
• Familiarity with DevOps workflows (e.g., Git, Azure DevOps) and orchestration tools like Airflow.
• Solid understanding of data warehousing, data modeling, and modern data architecture.
• Strong communication skills and the ability to work cross-functionally.

What's On Offer

• The opportunity to work with cutting-edge Azure data technologies.
• A hybrid working model offering flexibility.
• A role with significant impact on data infrastructure and decision-making.
• Collaboration with diverse product, analytics, and engineering teams.

Apply via Haystack today!