Design, develop, and maintain scalable data pipelines and data platforms supporting enterprise analytics, artificial intelligence (AI), and manufacturing operations.
Responsibilities
Design, develop, and maintain scalable data pipelines supporting Data Lakes, Lakehouses, Data Warehouses, and AI-driven platforms
Build and optimize ETL/ELT pipelines using Azure Data Factory, Azure Synapse, Microsoft Fabric, and related technologies
Develop Python scripts and SQL queries for data extraction, transformation, integration, and automation
Use Azure DevOps to streamline pipeline deployments, version control, and development processes
Design scalable data models to support enterprise reporting, analytics, and AI initiatives
Assist with the design, production, and maintenance of data pipelines and software infrastructure to support epidemiological research and public health policy.
Build, test, implement, enhance, maintain, and support data pipelines within the cloud OCC_Telestroke workgroup and related analytical or operational systems.
Design and maintain bidirectional data movement between the enterprise Corporate Data Warehouse (CDW), cloud workgroups, and operational systems, including source-of-truth logic, conflict resolution, and synchronization integrity.
Develop reproducible, version-controlled, and auditable ETL/ELT logic using SQL or Spark SQL, PySpark, and Python.
Designs, develops, implements, administers, and maintains data integration solutions, ETL/ELT pipelines, cloud infrastructure, data warehouse objects, and supporting applications across Palmer College of Chiropractic.
Responsibilities
Build and support reliable ETL/ELT pipelines and integrations
Administer and enhance Snowflake data structures
Prepare governed data for reporting, analysis, and institutional decision-making
Support data migrations and system implementations
Designs, develops, implements, administers, and maintains data integration solutions, ETL/ELT pipelines, cloud infrastructure, data warehouse objects, and supporting applications across Palmer College of Chiropractic.
Responsibilities
Build and support reliable ETL/ELT pipelines and integrations
Administer and enhance Snowflake data structures
Prepare governed data for reporting, analysis, and institutional decision-making
Support data migrations and system implementations
Develop and deliver scalable transformation frameworks across Hadoop platforms by building robust data pipelines, ingestion frameworks, and automation capabilities.
Responsibilities
Design, develop, and maintain scalable data pipelines within the Enterprise Data Lake platform using Cloudera CDP, Hadoop, Spark, Hive, Java, Python, and SQL.
Develop high-performance batch and near real-time data ingestion frameworks for onboarding enterprise source systems into the Data Lake.
Develop complex transformation logic using Spark, HiveQL, SQL, and Java-based processing frameworks.
Design and implement data ingestion patterns supporting structured, semi-structured, and unstructured datasets.
Build and maintain batch and near real-time data integration solutions.
Lead the design and delivery of scalable, governed data products on a Databricks Lakehouse across Azure and AWS.
Compensation
Pay Range: $133,365.00 - $156,900.00
Responsibilities
Lead and guide Databricks data engineering across Bronze, Silver, and Gold layers, with particular focus on trusted, reusable Silver and Gold data products.
Translate business requirements into scalable data architecture, engineering designs, delivery standards, and technical acceptance criteria.
Remain hands‑on in engineering and development, including coding, code review, and code management, while guiding the delivery of batch, CDC, streaming, API, and file‑based data pipelines.
Review data models, solution designs, and critical code for quality, security, scalability, performance, and alignment with engineering standards.
Drive cross‑cloud data integration and sharing across Azure, AWS, Databricks, and Snowflake.
Lead the design, development, governance, and operational support of enterprise data solutions for Beef & Pork Analytics.
Responsibilities
Lead the design and implementation of data engineering solutions for Beef & Pork Analytics
Translate business requirements into scalable data models, pipelines, and analytics-ready datasets
Develop, enhance, and support data products for Fresh Meats reporting use cases
Build and orchestrate complex ETL/ELT pipelines
Support DB2, SAP, USDA, and other data-source integrations into Data@Tyson/GCP
Requirements
Bachelor’s Degree in Computer Science, Information Systems, Data Engineering, Analytics, or related field, or equivalent combination of education and relevant experience
As a Senior Data Engineer, you will play a key role in designing, building, and evolving enterprise-scale data platforms that enable data-driven decision-making and advanced analytics.
Responsibilities
Design and implement scalable Data Lake and Data Warehouse architectures on AWS.
Develop and maintain robust ETL/ELT pipelines using Python, SQL, Spark, and AWS services.
Integrate data from multiple sources including APIs, databases, files, and enterprise applications.
Optimize data processing workflows for performance, scalability, reliability, and cost efficiency.
Implement data quality, governance, lineage, and security controls across the data ecosystem.
Implement patient-matching and record-linkage logic using multiple identifiers, including audit processes that protect data integrity.
Harmonize datasets across facilities and sources using consistent keys, date ranges, formats, naming conventions, and automated validation checks.
Requirements
Bachelor’s degree (5 additional years of relevant experience may be substituted for degree)
Nice to have: Current VA credentials, including an active PIV card
Nice to have: Experience supporting VA, VHA, another Federal health agency, or a large integrated healthcare system
Nice to have: Hands-on experience with Azure Databricks, PySpark, Python, SQL/Spark SQL, and Power BI, including Power BI report development using Databricks Spark SQL
Nice to have: Experience with applications and technologies used for automation, including Salesforce, Red Hat products, or comparable platforms relevant to the environment
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