- Design develop and maintain scalable ETL/ELT data pipelines using Azure Data Factory and Azure Databricks.

- Develop data ingestion and transformation workflows using Python SQL and PySpark.

- Work with Apache Spark and PySpark for large-scale distributed data processing.

- Implement batch processing incremental loading full loading and Change Data Capture (CDC) mechanisms.

- Integrate data from multiple sources including relational databases APIs and cloud storage.

- Work with Azure Data Lake Storage Gen2 and Azure Blob Storage.

- Develop and optimize data models fact tables dimension tables and data warehouse structures.

- Perform data cleansing validation deduplication and aggregation.

- Implement and manage workflows using Azure Data Factory and Apache Airflow.

- Optimize SQL queries Spark jobs and data pipelines for better performance.

- Work with Azure Synapse Analytics and relational databases.

- Implement error handling logging monitoring and alerting for production pipelines.

- Manage version control and CI/CD pipelines using Git GitHub and Azure DevOps.

- Troubleshoot production issues perform root cause analysis and provide production support.

- Maintain technical documentation and collaborate with cross-functional teams.

Requirements

Programming Languages

- Python SQL PySpark.

- Pandas NumPy OOP concepts exception handling and API integration.

Big Data Technologies

- Apache Spark and PySpark.

- Spark DataFrames Spark SQL transformations actions joins aggregations and window functions.

- Partitioning caching and performance optimization.

Azure Cloud Technologies

- Azure Data Factory (ADF).

- Azure Databricks.

- Azure Data Lake Storage Gen2 (ADLS Gen2).

- Azure Blob Storage.

- Azure Synapse Analytics.

- Azure Key Vault and Azure Monitor.

ETL & Data Engineering

- ETL/ELT pipeline development.





- Data ingestion transformation and migration.

- Change Data Capture (CDC).

- Incremental loading and full loading.

- Batch and distributed processing.

Database Technologies

- Microsoft SQL Server PostgreSQL MySQL and Oracle.

- Complex SQL queries indexing stored procedures and query optimization.

Data Modeling & Warehousing

- Dimensional and relational data modeling.

- Fact and dimension tables.

- Data normalization and denormalization.

- Schema design and data warehouse development.

Workflow Orchestration & DevOps

- Azure Data Factory and Apache Airflow.

- Git GitHub Azure DevOps and CI/CD pipelines.

File Formats

- CSV JSON XML Parquet and Delta Lake.

- 45 years of relevant experience in Data Engineering.

- Solid hands-on experience with Azure Data Factory Azure Databricks PySpark Python and SQL.

- Experience developing and optimizing scalable data pipelines.

- Good understanding of cloud-based data engineering and data warehousing concepts.

- Strong analytical debugging and problem-solving skills.

- Good communication and collaboration skills.

Required Skills:

Programming Languages Python SQL PySpark. Pandas NumPy OOP concepts exception handling and API integration. Big Data Technologies Apache Spark and PySpark. Spark DataFrames Spark SQL transformations actions joins aggregations and window functions. Partitioning caching and performance optimization. Azure Cloud Technologies Azure Data Factory (ADF). Azure Databricks. Azure Data Lake Storage Gen2 (ADLS Gen2). Azure Blob Storage. Azure Synapse Analytics. Azure Key Vault and Azure Monitor. ETL & Data Engineering ETL/ELT pipeline development. Data ingestion transformation and migration. Change Data Capture (CDC). Incremental loading and full loading. Batch and distributed processing. Database Technologies Microsoft SQL Server PostgreSQL MySQL and Oracle. Complex SQL queries indexing stored procedures and query optimization.

📌 Senior Data Engineer (Coimbatore)
🏢 InFynd
📍 Coimbatore