Description

·      Design and lead enterprise-grade pipelines, supporting both batch and streaming data processing;

·      Own the full ETL/ELT lifecycle, from design through production support;

·      Drive data engineering standards, best practices, and architecture across the data ecosystem;

·      Translate business requirements into scalable, high-performance data solutions;

·      Mentor a small team while remaining hands-on; and

·      Ensure data reliability, performance, governance, and cost optimization.

Qualifications:

·      10+ years of IT experience, including deep expertise in data engineering & ETL;

·      4-6+ years of recent hands-on experience in designing, building, and scaling data pipelines;

·      Strong hands-on experience with Databricks (Spark, Delta Lake, Unity Catalog) and AWS (S3, IAM, networking);

·      A passion for continued learning and an interest in staying current with the rapidly evolving data and analytics space;

·      Experience working in an Agile analytics environment where close collaboration with key stakeholders to address evolving requirements is the norm;

·      Expertise in SQL, Python, data modeling, and distributed processing;

·      Experience with CI/CD, DevOps, and modern data architecture (lakehouse, medallion, etc.); and

·      Strong communication skills and the ability to translate complex technical concepts into solutions that deliver business outcomes

Key Skills

Education

Any Gradute