969 Sr Data Etl jobs in Dallas,TX

Degree or equivalent experience
Typically requires 9+ years of professional experience and 1+ years of supervisory and/or management experience
9+ years in data management, data product management, or technical product management—preferably in healthcare, life sciences, or health tech
Proven experience leading product owners or managing multiple complex workstreams
Expertise with JIRA, Confluence, and Agile practices
Strong capability in writing/refining user stories and acceptance criteria
Strong experience translating business needs into data management requirements and actionable technical tasks
Familiarity with data ingestion, ETL, integration, and reconciliation of multi-modal healthcare datasets
Demonstrated success collaborating across engineering, data science, and business stakeholders in highly matrixed environments
Strong communication skills, with the ability to influence and partner at all levels
Strategic thinker with the ability to drive near-term delivery while shaping long-term platform evolution
Operates with strong ownership, accountability, and a mindset of automation, simplification, and continuous improvement
Up to 10% travel nationwide

CHRISTUS Health

Irving, TX 75039

McKesson

Irving, TX 75039

Master's in engineering & science or Equivalent experience
15+ years of professional experience
10+ years of management experience
Deep expertise in Microsoft Azure data services ecosystem (Azure Data Factory, Synapse Analytics, Data Lake Storage, Event Hubs, Cosmos DB)
Advanced proficiency with Databricks platform and advanced analytics workflows
Extensive experience with BI development, administration, and enterprise deployment
Strong foundation in modern data architectures: data lakes, data warehouses, real-time streaming, and event-driven systems
Proficiency in multiple programming languages (Python, Scala, SQL, .NET) and infrastructure-as-code practices
Proven success leading digital transformation and complex technology initiatives
Demonstrated ability to build and scale enterprise-grade data engineering organizations
Experience with P&L; responsibility, budget management, and technology ROI optimization
Strong understanding of enterprise data governance, regulatory compliance, and data privacy requirements
Proven ability to communicate complex technical concepts to executive stakeholders and non-technical audiences