Top Data Engineer Jobs in Chicago, IL

The AI Data Engineer will develop datasets for training and testing AI models, collaborating with engineering teams to define data specifications, optimize processes, and ensure data integrity. Attention to detail and automation of workflows are crucial in managing data acquisition, annotation, and conversion.

The Data Engineer will manage enterprise data assets, develop data pipelines, and storage solutions, while collaborating with business groups to optimize data use across the organization. Key responsibilities include designing high-performance data pipelines, maintaining data governance, mentoring team members, and implementing security measures for data storage. Expertise in Azure technologies and strong skills in SQL and Python are required.

As a Managed Services Informatica Data Engineer, you will design and implement ETL data pipelines, collaborate with cross-functional teams, ensure data quality and integrity, and contribute to client engagements while developing your skills.

As a Senior Associate in PwC's Data and Analytics team, you will design and build ETL jobs using Informatica PowerCenter, analyze problems, mentor team members, and maintain high standards. The role emphasizes client relationship-building and a deep understanding of the business context while navigating complex situations.

The Senior Associate Data Engineer will design, develop, and maintain data solutions focusing on integration and quality. Responsibilities include contributing to design decisions, managing risks, and supporting agile processes. Technically skilled in data integration, security, and pipelines, this role supports onboarding junior engineers and engages in agile ceremonies.

The Sr. Data Engineer will develop and operationalize a modern data environment, building infrastructure as code, designing ETL solutions, and collaborating with teams for data extraction, storage, and reporting. Responsibilities include maintaining data warehouse compliance, managing analytics tools, and supporting data-related issues. The role demands a focus on quality practices and participation in disaster recovery strategy design.

The Lead Data Engineer will expand and optimize data and data pipeline architecture, create data pipelines, support QA testing, and design BI datasets for reports. They will ensure data delivery architecture is effective and engage in data analysis using various tools, while also documenting all project phases and requirements.

As a Senior Data Engineer at Arcadia, you will develop solution architecture and data pipeline connectors for healthcare data integrations. You will contribute to the key responsibilities of designing, testing, and documenting ingestion pipelines, and partake in Agile processes within a Scrum team while ensuring the project timelines are met. You will also engage in peer code reviews and work directly with clients on data solutions.

As a Staff Data Engineer, you will design and implement scalable data pipelines, optimize data infrastructure, support BI product development, and ensure alignment with business goals while managing data workflows and collaborating with stakeholders.

The Data Engineer collaborates with clients to build and maintain data systems, developing pipelines and preparing data for analysis. Responsible for leveraging cloud infrastructure and advising on technologies to enhance data processing, the role involves solving complex problems and ensuring optimal data architecture.

The Intermediate Data Engineer will enhance data clean room architecture and support marketing and media objectives through collaborative data modeling and agile development. Responsibilities include building features, optimizing pipelines, and engaging with product teams to meet project requirements.

Lead Data Engineer at Capital One working on collaborative agile teams to design, develop, test, and implement technical solutions using full-stack development tools and technologies. Responsibilities include working with machine learning, distributed microservices, and cloud-based data warehousing services to deliver robust solutions.

The role involves joining the Content Measurement Engineering team to work on product features and enhancements through ETL processes with Python and SQL, orchestration with Airflow, and API development with Go. Responsibilities include participating in the full lifecycle of advertising tech products and ensuring quality and reliability in data processing solutions.

Lead and contribute to the advancement of a modern data lakehouse, develop data models, manage project life cycle activities, collaborate with team members, and mentor other engineers. Must have experience with Databricks and proficiency in Databricks, Microsoft Azure Data Factory, Python, and t-SQL.

The Lead Data Engineer will collaborate across Agile teams to develop and implement robust technical solutions involving full-stack development, machine learning, and cloud-based data warehousing. Responsibilities include mentoring, participating in tech communities, performing unit tests, and ensuring the quality and performance of code across data-driven projects.

As a Lead Data Engineer, you'll develop and support complex technical solutions using Java and Python while collaborating with Agile teams. You'll build a Data Loading Orchestrator and leverage big data technologies to enhance data processing in low-latency environments, contributing to the financial empowerment of customers.

As a Lead Data Engineer at Capital One, you'll work in an Agile environment to design, develop, and support technical solutions. You'll collaborate with teams to create cloud-based applications using a range of technologies, including machine learning and distributed systems. Responsibilities include coding, unit testing, and mentoring junior team members.