Description

·      We are investing in the next evolution of our data, analytics, and artificial intelligence ecosystem. We are looking for a Lead Data Engineer who’s ready to do more than just build pipelines on Databricks and AWS.

·      You will help shape enterprise analytics strategy, influence architecture, and partner directly with the business to drive smarter decisions.

Why This Role?

This is a high-impact, high visibility role where you will:

·      Lead the design and implementation of a modern AWS + Databricks Lakehouse platform

·      Partner across IT, analytics, and business teams to turn data into decisions

·      Drive scalable, governed, high-performance data solutions

·      Influence how data powers analytics, reporting, and AI across the company

What You’ll Be Doing

·      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

·      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)

·      Highly proficient in Databricks' core architectural pattern, which combines the best elements of data lakes and data warehouses.

·    Familiar with advanced features like Unity Catalog (for governance), Delta Live Tables (DLT for pipelines), Databricks SQL, and workflow orchestration.

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

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

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

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

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

Key Skills

Education

Bachelor's degree