Description

You own the end-to-end data engineering lifecycle, from research and PoC through architecture, design, development, deployment, and maintenance.

Responsibilities

• Design, develop, and implement cross-domain, scalable data solutions for meaningful analytics.
• Layer instrumentation into development to monitor pipelines and detect data quality issues proactively.
• Build diagnostic tools to troubleshoot, maintain, and optimize data solutions in production.
• Drive tech debt reduction and transformation, including cloud and open-source adoption.
• Maintain high-quality documentation for data definitions, transformations, and processes.

Required Skills

• 10+ years of experience in Data Engineering with hands-on ETL/Pipeline Development.
• Proficiency in Python or Scala for data ingestion, preparation, and operationalization.
• Experience with Apache Spark and Azure DataBricks/Azure DataFactory.
• Expertise in cloud data warehousing using Snowflake or Azure Synapse.
• Familiarity with DevOps practices using Azure DevOps and GitHub.
• Experience building end-to-end architecture for Data Lakes, Data Warehouses, and Data Marts.
• Strong understanding of SQL and data integration techniques.

Key Skills

Education

Any Graduate