Senior Data Engineer – Databricks

Experience: 5+ YearsEmployment Type: Fixed-Term / Contract Role Summary Design and build scalable data platforms on Databricks to enable reliable analytics, reporting, and AI-driven insights. Ensure data is secure, governed, and accessible across the organization. Key ResponsibilitiesBuild and maintain data lakes/lakehouses, ETL/ELT pipelines, and integrations across enterprise systems.Develop data models and reusable datasets for analytics and AI use cases.Ensure data quality, governance, security, and compliance.Monitor, optimize, and automate data workflows for performance and cost efficiency.Collaborate with stakeholders and drive engineering best practices and improvements. Requirements5+ years in data engineering with strong expertise in SQL and Databricks (Spark, Delta Lake).Strong programming skills (Python/Scala) for data processing and automation.Hands-on experience with cloud platforms (Azure/AWS/GCP) and distributed data processing.Solid experience in building and optimizing ETL/ELT pipelines and orchestration tools (e.g., Airflow).Strong understanding of data modeling (dimensional/lakehouse) and data warehousing concepts.Experience with data governance, data quality frameworks, lineage, and security best practices.Familiarity with DevOps/DataOps practices (CI/CD, version control, testing, deployment).Experience integrating data from multiple enterprise systems (ERP, CRM, Finance, etc.).Strong troubleshooting skills across complex data pipelines and systems.Ability to design scalable, reliable, and cost-efficient data solutions.Good understanding of BI/analytics and AI/ML data consumption requirements.Strong communication skills with ability to work with cross-functional stakeholders.