Senior Data Engineer

Leads Design and Optimization of Data PipelinesDesigns, builds, and maintains complex, scalable ETL/ELT pipelines for structured and unstructured data.Leads integration of data from EHRs, financial systems, registries, and external data sources.Optimizes pipelines for performance, reliability, fault tolerance, and cost efficiency.Implements batch and nearreal-time data processing patterns as needed.Ensures pipelines meet regulatory, privacy, and security requirements (e.g., HIPAA).Owns Key Data Platforms and Architecture ComponentsServes as technical owner for specific data platforms, domains, or subject areas (e.g., clinical analytics, operational reporting).Designs and maintains data lake, warehouse, and data mart structures using cloud platformsDevelops and enforces data modeling standards, schema design, and partitioning strategies.Partners with IT and cloud teams to ensure availability, scalability, and disaster recovery readiness.Enables Advanced Analytics and Data ScienceBuilds curated, analytics-ready datasets and reusable data assets for analysts and data scientists.Collaborates with data science teams to support feature engineering, model training, and deployment workflows.Develops frameworks and patterns that improve self-service analytics and reduce ad hoc data requests.Supports experimentation and proof-of-concept work for predictive analytics and AI/ML use cases.Drives Process Improvement and Engineering Best PracticesLeads initiatives to improve data engineering workflows, including automation, monitoring, and CI/CD for data pipelines.Refactors legacy pipelines and infrastructure to improve maintainability and scalability.Establishes best practices for code quality, documentation, testing, and version control.Evaluates new tools and technologies and recommends adoption where appropriate.Mentors and Provides Technical LeadershipServes as a technical mentor to Data Engineer staff.Reviews code, pipeline designs, and architecture artifacts to ensure quality and consistency.Provides guidance on complex technical problems and helps unblock team members.Contributes to onboarding, internal training, and knowledge-sharing activities.Collaborates with Stakeholders and Leads Medium-to-Large InitiativesPartners with business, clinical, research, and operational stakeholders to translate requirements into technical solutions.Leads data engineering workstreams within cross-functional projects or agile squads.Communicates technical concepts, trade-offs, and risks to non-technical audiences.Supports planning, estimation, and prioritization of data engineering initiatives.MARGINAL OR PERIODIC FUNCTIONSSupports data integration efforts for new service lines, acquisitions, or system migrations.Participates in vendor evaluations and technical assessments.Assists with disaster recovery testing and business continuity planning.Contributes to grant proposals or research initiatives requiring advanced data infrastructure.Performs related duties as required.KNOWLEDGE / SKILLS / ABILITIESTechnical ExpertiseAdvanced proficiency in SQL and Python and related languages for data engineering.Strong experience with distributed data processing frameworks (e.g., Spark).Hands-on expertise with workflow orchestration tools (e.g., Airflow).Deep familiarity with cloud-based data platforms and services (AWS, GCP, or Azure/Fabric).Experience designing and optimizing data models for analytics and reporting.Data Governance and ComplianceStrong understanding of data governance, data quality, and security best practices.Experience working with regulated data, particularly healthcare or clinical data.Familiarity with healthcare data standards (e.g., HL7, FHIR) preferred.Problem Solving and Decision MakingAnalyzes complex systems to identify root causes and scalable solutions.Balances short-term delivery with long-term architectural sustainability.Makes sound technical decisions with limited ambiguity.Collaboration and LeadershipEffectively collaborates ac oss technical and non-technical teams.Provides constructive feedback and technical guidance to peers.Demonstrates ownership, accountability, and initiative. University of Texas at Austin