Top Senior Level Data Engineer Jobs in Chicago, IL

The Senior Director, Data Strategy at Bounteous will be responsible for leading cross-functional engagements, assessing client data maturity, providing data advancement recommendations, and building a team of trusted advisors. They must have 8+ years of relevant experience in digital, consulting, or analytics.

As a Senior Consultant at Analytics8, you will work with a variety of companies, managing and implementing BI and DWH projects. You will be responsible for managing small projects, gathering customer requirements, mentoring junior consultants, and contributing to upsell opportunities. The role requires advanced knowledge of BI/DW development methodologies, SQL, and experience with data engineering and analytics tools. Strong communication and project management skills are essential.

Own the design, development, and administration of advanced analytics dashboards and reporting and business intelligence tools. Collaborate with stakeholders and provide guidance for developing new datasets and analyses. Solve new and interesting problems.

Seeking an Executive Director, Data Products to drive monetization efforts for D/Cipher's intent targeting solution, curate deal packages, develop high-margin data products, and analyze campaign performance for pricing strategy. Responsibilities include developing new data products, partnering with stakeholders, analyzing performance, and collaborating cross-functionally. Qualifications include a Bachelor's degree, 5+ years of programmatic monetization experience, advanced knowledge of ad tech platforms, and strong strategic thinking skills.

Seeking a Senior Machine Learning Platform Engineer to join the Machine Learning Foundations team at a company focused on economic empowerment. Responsibilities include building self-service tooling for the model lifecycle, collaborating with internal teams, leading architectural discussions, mentoring teammates, and more.

Senior Software Engineer role at Atlassian's Central AI team, responsible for building and maintaining core infrastructure for machine learning models and pipelines. Involves solving complex infrastructure challenges, leading projects, and collaborating with internal teams. Required skills include Java, Kotlin, Python, AWS, Apache Spark, and basic understanding of Machine Learning projects lifecycle.

Design, develop and deliver data products to production, solve technical problems, define and extend data architecture standards, mentor team members, propose ideas for improvement, implement ETL processes, work closely with Data Scientists and Product Managers.