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Strong employer brand and metro location balanced by niche pharma/AWS data specialization lowers applicant density.
Requires specific Pharma Commercial domain knowledge plus AWS data engineering expertise, limiting cross-industry transferability.
Explicit 8+ years, 2+ years lead, and mandatory AWS/data stack and pharma domain knowledge create strict filters.
Design, develop, and optimize scalable data pipelines and ETL/ELT workflows on AWS using services like S3, Redshift, Glue, EMR, Athena, ensuring performance, cost efficiency, and scalability.
Lead technical strategy and standards for AWS data frameworks, including data lake, warehouse, governance, security, and compliance across batch and streaming architectures.
Provide hands-on technical leadership and mentorship to data engineering teams, managing task planning, code reviews, and collaborating with cross-functional teams to translate business needs into technical solutions.
8+ years of data engineering experience with at least 2 years in a technical lead or senior role.
Strong hands-on expertise in AWS data services including S3, Glue, Redshift, EMR, Lambda, Athena, Kinesis, and Lake Formation.
Proficient in Python and/or Scala programming, advanced SQL, and experienced with data orchestration tools like Airflow/MWAA or Step Functions.
Detailed knowledge of Pharma Commercial business data (sales, claims, Voice of Customer, Veeva CRM, IQVIA) and experience with data security, IAM policies, and compliance requirements (GDPR, HIPAA, SOC 2).
Experienced technical leader with a track record of designing and operating large-scale AWS-based data architectures focused on pharma commercial data.
Strong strategic operator who can set engineering standards, ensure best practices across data engineering teams, and drive technical decisions on tooling and architecture.
Comfortable working in a regulated pharma environment with deep domain understanding, able to collaborate effectively with diverse technical and non-technical stakeholders globally.