Back
Senior, niche Databricks/AWS data role in a metro consulting context yields moderate competition.
Platform-specific requirements (Databricks, dbt, AWS) limit cross-industry portability to medium.
Multiple explicit technical, platform, and seniority requirements make shortlisting strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own and lead end-to-end data engineering lifecycle including design, implementation, testing, security, governance, deployment, and production support.
Build and operate batch and streaming data pipelines at enterprise scale (10s to 100s TBs).
Provide technical governance through design reviews, standards, delivery assurance, and mentor junior engineers.
8+ years of hands-on data engineering experience including leadership on production platforms.
Strong coding skills in Python, Java, or similar languages plus strong SQL capability.
Experience with AWS, Databricks/Spark, dbt for transformations, Airflow (or equivalent) for orchestration.
Experience working in regulated or security-conscious environments; familiarity with relational databases such as Postgres or SQL Server.
Deep technical expertise in production-grade data pipelines focusing on data quality, validation, security, and real-time processing.
Experienced in multi-stakeholder environments involving BAs, Architects, Data Scientists, and end users with consulting or client-facing delivery background.
Able to influence design and technical decisions by explaining trade-offs and ensuring feasibility and delivery within commercial discussions.