Data/ETL Engineer
ascendion
Job Description
Technical Design
- Develop and maintain data pipelines and ETL workflows using Databricks and Airflow.
- Good understanding of Databricks Delta Live tables, and Unity Catalog
- Build frameworks and templates for ETL/ELT, for telemetry pipelines.
- Ensure cloud-native designs aligned with AWS platform best practices.
Governance, Security & Optimization
- Ensure data quality, integrity, and governance across data platforms.
- Optimize SQL queries and data models for performance and scalability.
- Implement monitoring and observability for data workflows.
Cross-Functional Collaboration
- Work closely with architects and leads to understand data requirements and build technical solutions.
- Collaborate with analytics and business teams to deliver actionable insights through BI dashboards and reports
AI/LLM Enablement (Advantage)
- Familiarity with Agentic AI concepts for automation, data quality validation, and metadata enrichment will be an added advantage.
Required Skills & Experience
- 8+years of experience in data engineering, with at least 3 years in Databricks.
- Hands-on expertise in:
- Databricks (PySpark, Spark SQL, Delta Lake, Unity Catalog, Delta Live tables)
- SQL for data modeling and query optimization
- AWS services (S3, Glue, Kinesis, Redshift, API Gateway, SNS, Lambda)
- Airflow for workflow orchestration
- Added advantage – DBT, Splunk, Atlan, Java, API, Power BI
- Strong analytical and problem-solving skills with attention to detail.