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Top Data Engineer Jobs in Pittsburgh, PA
The Senior Data Engineer at PNC will design and maintain scalable data pipelines and ETL processes, ensuring high performance and reliability. Responsibilities include collaborating with stakeholders, optimizing data architectures, monitoring workflows for data quality, and staying updated on industry trends. This role combines technical proficiency with leadership in mentoring junior engineers.
The Data Engineer at Arcadia will design, build and test data connectors and ingestion pipelines, contributing to the integration of client claim and clinical data platforms. Responsibilities include peer code reviews, sprint planning, and maintaining JIRA tasks. The role requires problem solving for coding and data analysis issues within a dynamic healthcare environment.
You will design and implement data pipelines for ETL processes, collaborate with teams to gather requirements, ensure data quality, and support client engagement and project tasks while engaging in continuous learning.
As a Senior Associate in the Data and Analytics team, you will design and build ETL jobs using Informatica PowerCenter, analyze complex problems, mentor team members, maintain deliverable standards, and foster client relationships to drive informed decision-making.
As a Data Engineer at Bonterra, you will design scalable data models, build data pipelines, and deliver analytical solutions to empower nonprofit clients. You'll collaborate with cross-functional teams, solve complex data challenges, and mentor colleagues to promote best data engineering practices.
As a Data Engineer at PNC's Enterprise Fraud Organization, you will design, support, and optimize data services, automate processes, monitor data availability, and ensure scalability and reliability of data solutions. You'll collaborate with stakeholders to meet business objectives and prepare data for analytics.
The Data Engineer will design and implement scalable analytics solutions, build data pipelines, and deliver impactful data models. They will work collaboratively with teams to develop insights that help nonprofit clients make data-driven decisions.
Develops and implements data services for multiple applications to meet business objectives and user requirements. Designs and builds data service infrastructure on multiple data platforms. Implements data migration and transformation activities to ensure data accuracy and security.
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The Marketing Technology Data Engineer will design and build data solutions for managing and integrating real-time and batch data, focusing on data quality and availability for enterprise clients. The role involves developing data pipelines, implementing CI/CD processes, and collaborating with teams to meet client needs while leveraging Google Cloud services.
As a Google Cloud Data Engineer Manager at PwC, you will design and implement data solutions leveraging advanced technologies. You'll oversee data infrastructure, develop data pipelines, mentor teams, and collaborate with stakeholders to deliver high-quality data insights while ensuring compliance with governance policies.
As a Senior Manager in Google Cloud Data Engineering at PwC, you'll design and develop data solutions, and implement data pipelines for clients. You'll lead teams, manage complex problems, and stay relevant in technology. You'll collaborate with stakeholders to align data strategies with business needs and ensure compliance with governance policies.
As a Principal Data Engineer, you will drive the direction of the Data Warehouse, design and optimize ingestion pipelines, and mentor team members. You will ensure data accuracy, monitor pipelines, comply with regulatory requirements, and collaborate with internal teams for comprehensive data integration.
Headway is seeking a Senior Data Engineer to help create access to affordable, quality mental healthcare across the United States. This role involves collaborating on data infrastructure design, partnering with product/engineering for best practices, creating data pipelines for business insights, and building real-time data pipelines in coordination with the Data Science team.
As a Data Engineer Manager at PwC, you will lead the design and implementation of robust data solutions, manage data integration and transformation projects, and mentor team members. Your responsibilities include project ownership, ensuring quality deliverables, and collaborating with stakeholders to meet business data needs while upholding technical standards.
As a Data Engineer at Vetcove, you will design and maintain scalable data pipelines and optimize data workflows using advanced methods like Large Language Models (LLMs). You will collaborate with backend engineers to ensure data integration and utilize databases for efficient data storage and querying.
The Google Cloud Data Engineer Manager at PwC leads the design and implementation of data infrastructure and solutions, develops data pipelines, and integrates data. This role involves mentoring team members, ensuring project success, and fostering collaboration with stakeholders to enhance data-driven decision-making.
As a Senior Manager in Google Cloud Data Engineering at PwC, you will design and implement data infrastructure solutions and develop data pipelines. You'll manage teams, coach staff, and leverage cloud technologies to enhance data architecture and compliance with governance policies, while acting as a strategic advisor for clients and developing solutions to complex challenges.
As a Data Engineering Manager at PwC, you will lead the design and implementation of data solutions, manage team performance, and enhance data architecture strategies. Your role involves developing data pipelines, integration, and transformation solutions while mentoring team members. You will ensure projects meet quality standards and collaborate with stakeholders to address data requirements, all while upholding PwC values and professional standards.
As a Senior Data Engineer at Arcadia, you will design and develop data pipeline connectors for healthcare data integration, manage technical documentation, participate in team projects, code reviews, and scrum ceremonies, while ensuring timely delivery of solutions and collaborating with various internal teams to enhance analytic capabilities.
The Data Engineer will design, implement, and maintain the data infrastructure for analytics and business intelligence at Endpoint. Responsibilities include developing ETL pipelines, managing data warehouses, ensuring data quality, and collaborating with cross-functional teams to optimize data workflows and support data-driven decision-making.
The Sr. Data Engineer-GCP designs, develops, and integrates data applications on Google Cloud Platform. Responsibilities include building data processing systems, automating data pipelines, leading unit testing, adhering to quality standards, and implementing process improvements. The role leverages machine learning and collaborates with internal and external resources to support reporting and analytics needs.
As a Senior Data Engineer, you will transform operational data into analytical data, perform data analysis, write schema changes, and maintain ELT pipelines. You will champion a data-driven culture and interface with internal clients to understand their data needs, alongside troubleshooting data issues.
As a Senior Data Engineer at Instacart, you will build and maintain data pipelines to support paid marketing campaigns, collaborating with cross-functional teams while ensuring high-quality scalable solutions. You will drive data-driven decisions and enhance marketing strategies.
The Associate Principal Engineer (Data Engineer) will focus on data integration and warehousing, translate client requirements into technical designs, and oversee architecture and design practices while ensuring adherence to best practices. The role involves problem-solving, POCs development, and collaboration with development teams in an Agile environment.
Lead data engineer role at Wipfli focusing on the continuous advancement of a modern data lakehouse. Responsible for translating requirements into effective data models, developing in data technologies, managing project life cycle activities, achieving/maintaining proficiency in required skills, and collaborating with team members.
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