Description

Key Skills: AWS, AWS Cloud, Databricks, Azure, Azure Databricks, Data Engineer, Azure SQL

Roles and Responsibilities:

• Design, build, and maintain scalable ETL/ELT data pipelines for structured and unstructured data sources.
• Develop and optimize data solutions using AWS and/or Azure services, including ingestion, processing, and storage.
• Build and manage data lakes and data warehouses; implement data modeling and transformation workflows.
• Optimize data processing performance and ensure data quality through monitoring, troubleshooting, and pipeline enhancements.
• Implement data security, governance, and best practices; support CI/CD workflows for data engineering assets.

Skills Required:

• 6 - 10 years of relevant experience in data engineering and analytics platforms.
• Strong experience in data engineering and building production data pipelines.
• Hands-on experience with AWS (Glue, S3, Redshift, EMR, Lambda, Athena) and/or Azure (Azure Data Factory, Azure Databricks, Synapse Analytics, ADLS).
• Strong SQL and Python skills with experience in Spark or PySpark for data transformations.
• Knowledge of ETL/ELT, data warehousing/data modeling, and distributed computing; familiarity with Git and CI/CD.

Good to Have:

• Experience with Snowflake.
• Knowledge of Apache Airflow, Kafka, or Hadoop ecosystem.
• Exposure to Power BI or Tableau.
• Experience with DevOps tools and Infrastructure as Code (IaC).

Education: Degree in Computer Science, Engineering, or related field (or equivalent practical experience)

Key Skills

Education

Any Graduate