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Strong employer brand but specialized Databricks/dbt skillset limits applicant pool.
Role requires Databricks, Delta Lake, dbt, and pharma dataset experience, limiting industry transferability.
Multiple mandatory technical requirements (Databricks, Delta Lake, AWS) and explicit 6+ years requirement.
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Own design, build, and scalability of analytics-layer transformations and semantic data models on Databricks Lakehouse, enabling trusted self-serve analytics products.
Drive architectural decisions and optimizations for Databricks and AWS data platforms focusing on performance, scalability, and cost efficiency.
Lead and mentor junior developers, enforce data governance standards, and collaborate directly with business stakeholders and analysts to define metrics and data models.
6+ years of hands-on experience in analytics or data engineering with strong expertise in Databricks, data modeling, and AWS.
Proficient in designing and implementing dimensional models, star/snowflake schemas, and managing Delta Lake optimized workloads.
Experienced with AWS core services such as S3, IAM, Glue, Lambda supporting data platforms.
Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related fields, or equivalent practical experience.
Experienced in full-lifecycle analytics engineering on Databricks environments, including modern frameworks like dbt and Unity Catalog governance.
Skilled at mentoring and coaching junior engineers with hands-on involvement in deliverables and code reviews.
Comfortable in translating complex technical data solutions into business-friendly explanations and working closely with cross-functional teams including analysts and data scientists.