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Strong employer brand, mid-level generalist data role, metro location, and common skillset increase candidate competition.
Core data engineering skills are transferable, though enterprise DW and Ab Initio experience slightly limit portability.
Explicit 5-8 years plus required SQL, Python and data engineering skills raise filtering strictness.
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Architect and lead design of scalable analytics data pipelines integrating diverse data sources (RDBMS, API, DataLake).
Evolve and maintain data warehouse technology stack including ETL orchestration, data modeling, and BI tooling to ensure performance and scalability.
Lead deployment and operational support of production-grade data pipelines, establish governance frameworks including data documentation and lineage for audit compliance.
5-8 years of experience in data engineering, analytics engineering, or related roles with leadership in enterprise-scale solutions.
Bachelor's degree in Computer Science, Data Engineering, Analytics, or equivalent practical experience is mandatory.
Proficiency in SQL, Python, and Shell scripting (e.g., Bash) required for pipeline development and operational automation.
Hybrid work model requiring minimum two days per week onsite at assigned TransUnion office location.
Experienced in leading cross-functional data initiatives driving alignment and business-critical outcomes.
Skilled in designing scalable, high-performance data systems and optimizing data architecture and infrastructure.
Familiarity with infrastructure-as-code (IaC), agile environments, and BI/analytics tools (e.g., Apache Superset, Tableau) to enhance deployment and stakeholder collaboration.