Data Engineer - (Internal)

Data Engineer

No of Positions:

Job Location:

Job Type:

Experience:

Key Responsibilities

• Design, develop, and maintain scalable data pipelines for batch and streaming workflows
• Implement robust ETL/ELT processes to extract data from various sources and load into data warehouses
• Build and optimize database schemas following best practices in normalization and indexing
• Create and maintain documentation for data flows, pipelines, and processes
• Collaborate with cross-functional teams to translate business requirements into technical solutions
• Monitor and troubleshoot data pipelines to ensure optimal performance
• Implement data quality checks and validation processes
• Build and maintain CI/CD workflows for data engineering projects
• Stay current with emerging technologies and recommend improvements to existing systems
  

Key Requirements

• Bachelor's degree in Computer Science, Information Technology, or related field
• Minimum 3+ years of experience in data engineering roles
• Strong proficiency in Python programming and SQL query writing
• Hands-on experience with relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra)
• Experience with data warehousing technologies (e.g., Snowflake, Redshift, BigQuery)
• Proven track record in building efficient and scalable data pipelines
• Practical knowledge of batch and streaming data processing approaches
• Experience implementing data validation, quality checks, and error handling mechanisms
• Working experience with cloud platforms, particularly AWS (S3, EMR, Glue, Lambda, Redshift) and/or Azure (Data Factory, Databricks, HDInsight)
• Understanding of different data architectures including data lakes, data warehouses, and data mesh
• Demonstrated ability to debug complex data flows and optimize underperforming pipelines
• Strong documentation skills and ability to communicate technical concepts effectively