Top Data Engineer Jobs in Phoenix, AZ

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

We are seeking a Data Engineer to design, build and optimize scalable data pipelines. Strong experience in Databricks, PySpark, and data warehouse concepts is required.

Design, build, and maintain ETL pipelines, databases, and data models to process healthcare claims and related data. Ensure data quality, analyze claims data for trends, and produce reports and visualizations for nontechnical stakeholders. Collaborate with policy and analytics teams to translate requirements into data solutions and improve data infrastructure and analytics capabilities.

Design, develop, and support the Data Warehouse and reporting systems. Build and optimize SSRS reports, Power BI dashboards, and SQL ETL/queries. Ensure data accuracy, maintain documentation, and mentor team members while collaborating with business units to translate requirements into scalable data solutions.

Build and maintain low-latency, highly available distributed data systems and services to deliver high-quality data for product, analytics, and ML. Partner with data scientists and product teams to design scalable, observable, multi-tenant data products using batch and real-time processing frameworks. Ensure 24x7 reliability, monitoring, and operational excellence while owning end-to-end delivery.

Build scalable, privacy-focused data frameworks and ETL pipelines using big-data technologies (Spark, Presto, Flink, Kafka, Hive). Ensure appropriate handling of personal data, support privacy and legal needs, partner cross-functionally, and lead system design while mentoring teammates.

Design, build, and own large-scale batch and streaming data pipelines and core Ads data products. Collaborate with analytics, data science, and engineering teams to model, transform, govern, and deliver high-quality ad datasets for analysis, ML, and reporting while ensuring privacy compliance.

Build and maintain scalable batch and real-time data pipelines, model data to power analytics and ML, and operate distributed data systems. Collaborate with business, engineering, and data science teams to ensure data quality, documentation, and debugging while adopting new technologies and working in an ambiguous, fast-changing environment.

Lead design and implementation of scalable cloud data lakes, warehouses, and marts. Build ELT/ETL pipelines, apply Data Vault 2.0 and dimensional modeling, implement data quality, lineage, observability, and governance. Optimize Snowflake/Databricks/Synapse platforms, champion CI/CD and DataOps, mentor engineers, and enable AI/ML-ready data products through collaboration with architecture and product teams.

Build and maintain data pipelines, applications, workflows, and governance within Palantir Foundry. Apply industrial engineering and operations research methods to analyze depot, MRO, and supply chain processes, integrate ERP/MRO data into models, run capacity/throughput analyses, deliver decision‑support briefings, and support adoption of advanced analytics and digital engineering. Coordinate with stakeholders and support business development activities.

Design, build, and optimize scalable Azure data platforms and lakehouse architectures. Develop ETL/ELT pipelines (PySpark/Spark SQL), enable Power BI datasets, implement CI/CD and IaC, ensure data governance/quality with Purview, support cloud migrations and production operations while collaborating with stakeholders and agile teams.

Build and implement a transactional data system: design and develop SSIS ETL packages, consume web services in ETL, create SSRS reports for ETL status, and implement T-SQL/SQL Server solutions per functional requirements and system design.

Design, build and maintain a data transactional system performing ETL and web service calls to synchronize state between systems. Develop SSIS packages, data models, dictionaries, test plans, and assist architects on database strategy.

Develop ETL, reporting, and OLAP solutions using SQL Server (SSIS, SSRS, SSAS) and T-SQL; perform impact analysis, document requirements, support ETL/data quality, and assist database architecture and defect resolution.

Implement OLTP and OLAP systems to persist court information from functional requirements and system design. Perform ETL, export data to external agencies, use managed service calls, design and model database structures, design/code/deploy SSIS packages, document data dictionaries and package definitions, develop SSIS test plans, and support architects.

Lead design and delivery of scalable, secure cloud data pipelines and products. Translate requirements into architecture, apply advanced data modeling (Data Vault 2.0/dimensional), embed data quality, observability, security, and DataOps/CI-CD practices, optimize performance and cost, mentor engineers, and enable AI/ML-ready datasets within an agile DevSecOps model.

Design, build, and operate scalable cloud data pipelines and platforms (Azure preferred). Implement DevSecOps, CI/CD, automated testing, monitoring, performance tuning, and production readiness. Mentor engineers, drive operational excellence, and translate requirements into robust technical designs. Apply healthcare domain knowledge and collaborate in agile teams to deliver secure, reliable data products.

The job involves building responsive web dashboards, advanced data visualizations, and analytics tools for unmanned aircraft systems, requiring a deep understanding of UI/UX design and data presentation.

The Data Engineer will build and maintain data platforms, deploy pipelines, monitor transformations, and collaborate with Data Scientists and DevOps.

Design, build, and optimize scalable Azure data platforms and lakehouse architectures. Develop ETL/ELT pipelines (PySpark, ADF, Fabric), enforce data governance and quality, enable Power BI reporting, lead cloud migration and CI/CD, and provide production support and performance tuning across enterprise data systems.

Lead design and delivery of production data platforms, pipelines, and analytics. Architect Snowflake/Databricks solutions, build ETL/streaming ingestion, implement dbt transformations, data quality, observability, and governance, support BI and AI/ML feature/data pipelines, and mentor engineers while driving DataOps and platform best practices.

Lead design, development, and administration of enterprise Power BI reporting, semantic models, and Azure-based data pipelines. Deliver executive dashboards, KPIs, advanced analytics, and governance; mentor teams and modernize BI capabilities while ensuring performance, security, and data quality across the organization.

As a Data Engineer, you will design and maintain data pipelines, support DoD systems, and ensure data quality and compliance.