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Tier-1 brand, metro location, mid-level generalist data role increases applicant competition.
Core data engineering skills are transferable across industries, but pharma governance and MDM add domain bias.
Explicit 5+ years and mandatory AWS/Databricks/PySpark and data modeling skills create strict filters.
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Build and maintain scalable data models and pipelines using AWS technologies to support business functions and downstream systems.
Collaborate with multiple business units and enterprise teams to improve data quality, integration, and support digital product development.
Ensure data reconciliation, monitor data quality, troubleshoot data issues, and support production data availability and accuracy.
Bachelor’s Degree in Engineering, Computer Science, or related field from an accredited institution.
5+ years (preferably 7+) of experience in data engineering, software development, data warehousing, and supporting digital products.
Strong expertise in data integration, data modeling, and AWS cloud technologies (including DMS, Lambda, Databricks, SQS, Step Functions, Data Streaming).
Experience working in AGILE SCRUM teams and familiarity with tools like JIRA and Confluence.
Experienced in operational data engineering with focus on scalable, cloud-native data pipelines and models, primarily on AWS.
Skilled collaborator with cross-functional teams including frontend/backend engineers, product managers, and enterprise architecture.
Proficient in DevSecOps practices, source-code versioning, and supports data governance frameworks.