Top Data Engineer Jobs in Phoenix, AZ

The Principal Data Engineer will lead data governance, architecture, and team development to unify data across systems while ensuring quality and compliance. Responsibilities include building data pipelines, establishing governance frameworks, and collaborating with cross-functional teams to drive data-driven insights and operational efficiencies.

Design, architect, and deliver services for Ensemble's products while collaborating with cross-functional teams and mentoring junior engineers.

The Data Engineer I is responsible for building reliable ELT/ETL pipelines, implementing data quality checks, and optimizing data models using dbt, while collaborating with stakeholders to ensure data reliability and consistency.

Lead and mentor a data engineering team to design and operate scalable ETL/ELT pipelines and Snowflake data warehouse solutions using Python, DBT, Matillion, and AI tools; establish standards, ensure data quality and governance, and collaborate with analytics, product, and BI stakeholders to deliver production-ready data platforms.

As a Data Engineer, you'll design and implement data pipelines on Google Cloud, manage cloud infrastructure, ensure data quality, and enable analytics for marketing insights.

The Data Engineer will design and maintain data pipelines, optimize SQL queries, implement data workflows, and ensure data quality. The role demands collaborative problem-solving and technical communication skills to support analytics and business intelligence efforts.

Design, build, and optimize ETL pipelines and data workflows. Collaborate with teams to translate requirements into data solutions, ensuring data quality and efficiency.

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.

Intern will gain hands-on experience in data engineering by working with technologies like Databricks, SQL, and Azure. Responsibilities include technical proficiency development and participation in AI projects.

The Principal Data Engineer will lead the Data Resolution team, focusing on complex data challenges using Spark, system architecture, and mentorship, to optimize graph data pipelines.

The Senior Data Engineer II will design and maintain scalable data pipelines, collaborate with teams on machine learning workflows, and ensure data accessibility across systems.

As a Data Engineer, you will build and optimize data pipelines, ensuring accurate data delivery that informs pricing and market analytics at Alt.

The Data Engineer will build and maintain data pipelines, optimize queries, collaborate with teams, and ensure data quality across Google Cloud systems.

The Lead Python Developer will design and develop Python-based analytics solutions, create reporting tools, collaborate with stakeholders, and mentor peers in a healthcare analytics environment.

The job involves leveraging AWS and Snowflake for data engineering tasks within a technology-focused company, requiring US residency.

Design, develop, and manage data infrastructure for internal and client projects, focusing on large-scale data pipelines, APIs, and cloud deployments.

The Lead Data Consultant will design and deliver scalable data solutions, manage project teams, and optimize client data environments, ensuring effective project execution and communication.

The Data Engineer will design and maintain data pipelines, optimize cloud data warehouses, and collaborate with analytics teams while mentoring junior staff.

The Senior Data Engineer will design scalable data processing frameworks using Java and Apache Spark, manage data pipelines, and mentor junior engineers.

The Data Engineer will design and maintain scalable data infrastructure and pipelines, ensuring data quality and security on Azure, while collaborating with client teams.

Design, build, and maintain scalable data pipelines and tooling to support AI and analytics. Manage datastores (MySQL, Redshift, OpenSearch), implement AWS-based ETL/ELT solutions, collaborate with data science and product teams, and ensure data quality, automation, and production reliability.

The Data Engineer will build and maintain data pipelines, ensuring high-quality and scalable data systems while working on analytics and machine learning accessibility.

The Data Solutions Engineer will architect data systems, build pipelines, ensure data governance, optimize performance, and mentor team members to support analytics and operational workloads.

The Senior Data Engineer will develop data engineering solutions, manage ETL workflows, and establish a new data practice while collaborating with stakeholders.

Lead design, build, and optimization of Sezzle's large-scale data warehousing and pipelines. Own data infrastructure KPIs/SLAs, improve Redshift performance, evolve the data stack, implement ETL/ELT workflows, and partner with cross-functional teams to deliver reliable, scalable datasets.