Senior Analytics Engineer

Overview

Senior Analytics Engineer to design, build, and scale the analytics layer on Databricks, turning curated data into trusted, self-serve analytics products for commercial reporting.

What you'll do

• Own analytics-layer transformation logic, including marts, semantic models, and metrics.
• Architect dimensional/semantic models and metrics definitions for governed, analytics-ready datasets.
• Set standards for data modeling and testing, including validation and CI/CD for analytics code.
• Tune performance and optimize Databricks and Delta Lake costs and workload efficiency.
• Design AWS-based Lakehouse data architecture with storage, IAM, Glue, Lambda, and security fundamentals.
• Drive technical design reviews and mentor junior developers in Databricks/AWS/data modeling.

What you'll need

• Core hands-on expertise in Databricks (notebooks, jobs/workflows, clusters, Unity Catalog) and Delta Lake.
• Strong-dimensional analytics data modeling experience (star/snowflake schemas, conformed dimensions, fact tables, SCD).
• Solid hands-on AWS experience supporting a Databricks Lakehouse (S3, IAM, Glue, Lambda, networking/security).
• Advanced SQL and Python for data transformation, modeling, and validation.
• Experience with analytics engineering frameworks (e.g., dbt) and building governed semantic/metrics layers.
• Experience with workflow orchestration (e.g., Databricks Workflows, Airflow) and CI/CD/code review via Git.
• Experience mentoring junior developers through pairing and pull-request/code review.