Engineer Jobs

About The Position

Requirements

• Bachelor’s degree in a related field and seven years of related experience, or an equivalent combination of education, training, and experience.
• Strong experience designing and maintaining data pipelines and ETL/ELT processes across multiple source systems.
• Proficiency in Python, SQL, and Apache Spark (PySpark).
• Experience with modern data platforms such as Azure Fabric, Azure Synapse Serverless, or Databricks.
• Ability to work with large, complex, and distributed datasets.
• Solid understanding of data-modeling concepts and best practices.
• Familiarity with data governance, metadata management, and data-quality frameworks.
• Ability to lead technical design discussions, review code, mentor engineers, and guide delivery across multiple workstreams.
• Experience with CI/CD practices and proficiency with version-control systems such as Git.
• Familiarity with data-pipeline orchestration and monitoring tools such as Airflow, Azure Data Factory, or similar frameworks.
• Strong analytical, problem-solving, and critical-thinking abilities.
• Strong communication and collaboration skills, including the ability to explain technical concepts to diverse audiences.
• Ability to prioritize engineering work, identify delivery risks, and adapt to changing business and platform requirements.
• Ability to manage workload effectively and report task status in a timely manner.
• Understanding of and ability to follow standard operational procedures and HIPAA regulations.

Nice To Haves

• Microsoft Fabric experience, including Lakehouse, Warehouse, notebooks, and data pipelines.
• Experience integrating higher education and healthcare enterprise HR, Finance, Student, and Research applications.
• Understanding of biomedical informatics methodologies.
• Experience applying biomedical informatics technical standards, methodologies, and principles to research-specific program needs.

Responsibilities

• Lead source-system onboarding and data integration from analysis and design through development, validation, deployment, and production support.
• Partner with architects to implement platform designs, reusable ingestion frameworks, and engineering standards aligned with UDP architecture and institutional priorities.
• Design, develop, and optimize ETL and ELT pipelines using SQL, Python, PySpark, Microsoft Fabric, or comparable cloud technologies.
• Analyze source schemas, business rules, and enterprise application dependencies; define source-to-target mappings, incremental load strategies, and reconciliation requirements.
• Guide implementation of bronze, silver, and gold data layers, including transformations, dimensional modeling, and curated datasets for reporting and analytics.
• Establish and review coding, testing, documentation, version-control, and deployment standards; conduct code reviews and mentor data engineers.
• Coordinate engineering tasks and technical dependencies with Business Analysts, Project Managers, Data Analysts, Architects, and source-system owners; communicate progress, risks, and resource needs.
• Implement data-quality checks, reconciliation controls, monitoring, alerting, error handling, and recovery procedures for reliable production processing.
• Troubleshoot complex pipeline and data issues; tune SQL, Spark workloads, and orchestration for performance, scalability, and efficient platform-capacity use.
• Apply institutional data-governance and security standards, including access controls, metadata, lineage, and appropriate handling of sensitive data; support HIPAA requirements where applicable.
• Translate stakeholder requirements into technical specifications and explain design choices and data limitations clearly.
• Create and maintain technical documentation, operational runbooks, source mappings, and support procedures; coordinate production deployments and knowledge transfer.
• Support existing UDP and Enterprise Business Intelligence integrations and services while balancing operational needs with project delivery priorities.
• Evaluate emerging technologies, develop focused proofs of concept, and promote technologies that address identified business or engineering needs.
• Work as a positive member of cross-functional projects to deliver quality applications and components within scope, schedule, and budget, and ensure compliance.
• Manage workload, report task status in a timely manner, guide stakeholders on solutions and support structures, and help prioritize partner work.
• Form tactical strategies to support multiple clients and lead small- to medium-sized technical teams; mentor analysts on regulatory adherence.
• Follow standard operating procedures and HIPAA regulations; maintain data standards and metadata for complex datasets.
• Apply biomedical informatics technical standards, methodologies, and principles to research program needs, objectives, and outcomes.
• Develop reporting infrastructure for multiple client needs and generate standard architecture-documentation templates for current and proposed informatics solutions.
• Perform other related duties as required.