Design, build, test, maintain, and monitor scalable Lakeflow Spark Declarative Pipelines using Event Hubs and medallion architecture. Gather requirements, transform data across pipeline layers, troubleshoot complex issues, and create technical documentation. The role requires proficiency in Python, SQL, PySpark, Spark SQL, Databricks, Azure, and Unity Catalog, with streaming and declarative pipeline experience preferred.
Sr. Data Engineer
Data Engineer with 4+ years of experience in SQL, PySpark, ETL, ADLS, Azure Databricks, Unity Catalog, and Azure technologies.
Responsibilities- 3+ years of experience developing data pipelines using Python/PySpark, with proficiency in Spark SQL and Azure Databricks.
- 4+ years of experience with Azure data engineering technologies, including ADLS, Unity Catalog, Azure Data Factory, Azure Databricks, and Azure SQL/Synapse.
- 4+ years of experience with SQL.
- Experience in data modelling, including dimensional modelling, star schema and snowflake schemas.
- Proficiency in version control tools such as Git and project management tools such as Jira.
- Excellent verbal and written communication skills.
- UG: B.Sc, BCA, or B.Tech/B.E. in any specialization.
- Reliable internet connectivity is required.
- Experience working with financial data or finance-related datasets.
- Experience with Structured Streaming and Azure Event Hubs.
- Experience with Declarative Automation Bundles and Spark Declarative Pipelines (SDP).
- Azure certifications.
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