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Mid-level, popular data-engineer role in a metro with moderate brand and broad skill requirements.
Enterprise data-warehouse and Ab Initio requirements create moderate industry-specific sensitivity.
Explicit 5-8 years requirement plus mandatory data engineering skills and platform experience.
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Own and lead architecture, design, and delivery of scalable, enterprise-level data analytics pipelines and ecosystems supporting transactional and analytical workloads.
Define and enforce engineering standards for data ingestion, transformation, and reporting to ensure data consistency, quality, and governance across teams.
Lead deployment, monitoring, and operational support of production-grade data pipelines to ensure uptime, performance, and adaptability.
5-8 years of experience in data engineering, analytics engineering, or related roles with leadership in enterprise-scale data solutions.
Bachelor’s degree in Computer Science, Data Engineering, Analytics, or equivalent practical experience.
Proficiency in SQL, Python, and Shell scripting is mandatory.
Hybrid work model requiring minimum two days per week onsite at TransUnion office.
Experienced in evolving technology stacks involving ETL orchestration, data modeling, and BI tools such as Apache Superset.
Demonstrated ability to lead cross-functional data initiatives and translate complex business requirements into scalable technical solutions aligned with strategic objectives.
Familiarity with infrastructure-as-code (IaC), agile environments, and production-grade pipeline operational excellence.