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Data Engineering Manager

MathCo

Chicago, ILFull time5-10 yearsNot Disclosed

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Job Description

Role Description

  • We are seeking a Data Engineering Manager with expertise in the CPG domain and hands-on knowledge of Azure Cloud technologies. Based in the UK, you will lead client-facing programmes, guide engineering teams, and ensure scalable, modern data solutions are delivered to support supply chain, sales, and consumer analytics for global CPG clients.
  • This role blends programme leadership, client engagement, and technical direction, requiring someone who can translate business objectives into data strategies, coach teams, and ensure delivery excellence


Job Responsibilities

  • Leading Partner with CPG stakeholders to align data engineering solutions with supply chain, sales, and marketing priorities.
  • Define solution architectures and oversee end-to-end data pipelines, ETL/ELT processes, and data platform implementations.
  • Guide teams in applying best practices across Python, SQL, Databricks, and Delta Lake to deliver high-performance outcomes.
  • Manage client programmes, ensuring projects are delivered on time, within scope, and aligned to strategic goals.
  • Promote engineering standards, agile ways of working, and CI/CD adoption across teams.
  • Act as a trusted advisor, simplifying technical concepts and communicating clearly with business stakeholders.
  • Develop and maintain data pipelines using Azure ADF, Databricks, PySpark, and Delta Lake.
  • Build and optimise workflows in Python and SQL to support supply chain, sales, and marketing analytics.
  • Contribute to CI/CD pipelines using GitHub Actions (or similar) for deployment and testing.
  • Monitor production data workflows, provide troubleshooting support, and resolve performance issues.
  • Work with managers and architects to translate business requirements into technical designs and solutions.
  • Apply engineering best practices including version control, testing, and code reviews.
  • Document solutions and share learnings across the team



Required Qualifications

  • 12+ years of experience in data engineering, with at least 4+ years in a leadership/programme management role.
  • Domain expertise in CPG analytics.
  • Strong experience with AI, Azure Data Factory, Databricks, Event Grid, Python, and SQL.
  • Proven background designing and overseeing enterprise-scale pipelines and platforms.
  • Familiarity with CI/CD processes (GitHub Actions or similar).
  • Excellent communication, stakeholder management, and coaching skills.
  • Bachelor’s degree in Computer Science, Engineering, or related field.
  • Consulting background with Fortune 500/Global 2000 client delivery experience.

About The Company

MathCo

TheMathCompany or MathCo® is a global Enterprise AI and Analytics company, trusted for data-driven decision making by some of the largest organizations across industries. Founded in 2016, MathCo builds custom data products through its innovative hybrid model and transfers the ownership of intellectual properties to its clients. NucliOS, MathCo’s proprietary platform with pre-built workflows and reusable plug-and-play modules, enables the vision of connected intelligence at a lower TCO. MathCo’s full-stack team provides a holistic range of services spanning strategy, advanced analytics, data engineering and governance, MLOps, GenAI, data visualization, and adoption advisory services. MathCo’s numerous accolades include recognitions in Gartner’s Magic Quadrant for D&A Providers, Everest Group’s Peak Matrix Assessment, and being listed as a Great Place to Work. To know more about how MathCo supports organizations to own and activate intelligence, visit our website.

Company Size1000-5000
Founded2016
HeadquartersChicago, Illinois
IndustryBusiness Consulting and Services
TypePrivately Held
SpecialitiesAdvisory services, Problem Solving, Design Capability, Advisory Services, Data Visualisation, Business Intelligence Solutions, Advanced Analytics, Analytics Consulting, Machine Learning, Data Management, AI Consulting, Customer Analytics, Data Engineering, Data Science, Product Engineering, Supply Chain Analytics, Customer Experience Analytics, AI Engineering, Predictive Analytics, Forecasting, Optimization, Natural Language Processing, AI/ML Ops, and Modern BI & Data Warehousing

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