Azure Data Engineer
2 weeks ago
Key Responsibilities
- Design, build, and maintain a robust data platform on Databricks.
- Develop efficient ETL/ELT pipelines to ingest data from SQL Server, MongoDB, and
InfluxDB into Databricks Delta Lake.
- Implement real-time and batch data ingestion strategies using tools such as Kafka,
Azure Event Hubs, or similar.
- Optimize data storage and processing for performance, scalability, and
cost-effectiveness.
- Build data models to support BI, advanced analytics, and machine learning use cases.
- Collaborate with stakeholders (Data Scientists, Analysts, Product Teams) to define data
requirements.
- Ensure data quality, governance, and security across the platform.
- Monitor, troubleshoot, and enhance data workflows for reliability.
Required Skills & Qualifications
- Proven experience in Databricks (Delta Lake, Spark, PySpark, SQL).
- Strong expertise in data integration from multiple sources (SQL Server, MongoDB,
InfluxDB).
- Hands-on experience with ETL/ELT pipeline development and orchestration (e.g.,
Airflow, ADF, or equivalent).
- Proficiency in data modeling, data warehousing concepts, and performance tuning.
- Familiarity with real-time data streaming (Kafka, Azure Event Hubs, or similar).
- Strong programming skills in Python and SQL.
- Experience with cloud platforms (Azure).
- Excellent problem-solving skills and the ability to work in a fast-paced environment.
- Familiar with Change Data Capture
Preferred Qualifications
- Experience with InfluxDB or time-series data handling.
- Exposure to machine learning workflows within Databricks.
- Knowledge of data governance frameworks (Unity Catalog, Purview, or similar).
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