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Mid-level Snowflake specialist in metro with moderate brand and specific skills attracts medium competition.
Snowflake and data engineering skills are transferable, though life-sciences preference increases domain specificity.
Multiple mandatory years, Snowflake expertise, ETL/orchestration skills and consulting experience make shortlisting strict.
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Lead design and delivery of Snowflake-based Data Management solutions end-to-end for life sciences clients.
Translate business/data requirements into data models, technical designs, transformation logic, and implementation plans, owning technical workstreams from development through deployment.
Enable and guide L1/L2 team members, lead troubleshooting, and manage client interactions around solution design, implementation, and operational readiness.
Bachelor’s or Master’s degree in Computer Science, Engineering, IT, or related field.
5–7 years experience in data engineering, data warehousing, data management or consulting.
4+ years strong hands-on Snowflake experience including Streams, Tasks, Snowpipe, micro-partitioning, and clustering.
Strong SQL and Python skills; familiarity with ETL/ELT (e.g. dbt, Informatica) and orchestration tools (e.g. Airflow); ability to support US clients during US working hours.
Proven ability to independently lead technical workstreams with hands-on Snowflake expertise in a consulting or client-facing environment.
Experience designing scalable Snowflake solutions with strong grasp of query optimization, workload management, and data warehouse architecture.
Domain experience in life sciences, pharmaceutical, or healthcare data with familiarity in commercial/customer data, MDM, data quality, and governance preferred.