Top Data Engineer Jobs in Pittsburgh, PA

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.

As a Lead Enterprise AI Data Engineer, you will design and build scalable data pipelines and AI tooling, enabling data-driven decision making in collaboration with business stakeholders and data scientists.

As a Data Engineer, you will design and maintain data pipelines, build data storage systems, and support analytics workflows, ensuring data reliability and performance. You will collaborate with engineers to define data structures and improve data management practices.

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.

As the first in-house Data Engineer, you will own the data infrastructure, build and maintain data pipelines, and collaborate with teams to ensure quality data access and insights.

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

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.

Develop scalable data architecture for targeting and engagement, optimize pipelines, lead technical projects, and maintain data quality and documentation in a fast-paced political environment.

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 Data Engineer will design and maintain ETL/ELT pipelines, optimize data processing jobs, and ensure data quality and availability.

As a Data Engineer, you will build and maintain data ingestion pipelines, develop data transformations, and migrate SQL Server processes to Azure-native solutions, supporting marketing campaigns and analytics teams.

Design, build, and optimize data pipelines for analytics and ML. Collaborate with BI teams and improve data platform performance.

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

As a Data Engineer, you'll build and maintain data architectures, develop scalable data pipelines, and optimize data systems to support analysts and data scientists. Responsibilities include designing databases, implementing ETL processes, and collaborating with teams to ensure efficient data workflows.

The Looker Data Engineer will build and optimize data models, develop reporting solutions, and support data-driven decisions using Looker and other technologies.

The Senior Data Engineer will build and maintain data pipelines, optimize data processing, and ensure data privacy and quality within the healthcare tech space.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

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

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

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.

As a Data Engineer, you will build and maintain data pipelines, ensure data quality, support ML workflows, and optimize query performance using various technologies.

The Principal Data Engineer will design and maintain data systems, evaluate technology solutions, mentor team members, and communicate effectively with stakeholders.