Sr. Associate / Consultant / Manager (Data Engineering)
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Protocol Intelligence
Data-driven signals on your job's competitivenessMid-level metro Data Engineer role with generalist stack, but pharma/domain specificity reduces competition.
Core data engineering skills transferable, but pharma domain experience increases fit sensitivity.
Explicit 4+ years, mandatory SQL/Python/PySpark and AWS/Snowflake skills increase screening strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Build, maintain, and optimize ETL/ELT pipelines for pharma data sources to enable integrated data insights.
Perform exploratory data analysis, troubleshoot data issues, and implement data quality mechanisms to ensure data accuracy.
Develop and manage data solutions including data models and ETL processes, while applying best practices and documentation for efficiency.
Minimum Requirements
4+ years of relevant industry experience as Data Engineer.
Bachelor’s or Master’s degree in Engineering, MCA, or equivalent.
Hands-on experience with SQL, Python, PySpark, and AWS services (S3, Glue, Lambda, CloudWatch, Athena).
Working experience in pharma domain and familiarity with Dataiku and Snowflake.
Ideal Candidate Profile
Experienced in managing complex data engineering tasks within the pharma sector, with focus on ETL optimization and data quality.
Comfortable working with cloud-native data platforms, especially AWS, and proficient in programming for data workflows.
Capable of independently troubleshooting data issues and proactively documenting processes to improve team efficiency.