Company:A Large Global Organization

Key Skills: Pyspark, Azure Databricks, SQL, Medallion Architecture, PowerBI, Python

Roles and Responsibilities:
Design, build, and maintain scalable ETL and ELT pipelines using Azure Databricks and PySpark.
Ingest and transform structured, semi-structured, and unstructured data from enterprise source systems.
Develop curated Delta Lake data models across medallion architecture layers for analytics and AI/ML consumption.
Implement data quality controls, operational metadata, auditability, lineage, reconciliation, and exception handling.
Support governed access to lakehouse data and resolve pipeline, data quality, and delivery issues in collaboration with downstream consumers.

Skills Required:
5 - 8 years of relevant experience in data engineering and lakehouse development.




Hands-on experience developing production data pipelines with PySpark and Azure Databricks.
Solid SQL skills for data transformation, validation, analysis, and performance tuning.
Practical experience implementing medallion architecture and curated lakehouse data layers.
Experience building scalable ETL/ELT pipelines, Delta Lake models, data quality controls, and analytics-ready datasets.

Valuable to Have:
Experience with Power BI and Python for analytics enablement, data preparation, or supporting downstream data products.

Education: Any graduate degree; any academic branch considered.

📌 Data Engineer 105345 Bengaluru (India)
🏢 MyCareernet
📍 India