Huron is a global consultancy that collaborates with clients to drive strategic growth ignite innovation and navigate constant change. Through a combination of strategy expertise and creativity we help clients accelerate operational digital and cultural transformation enabling the change they need to own their future.

Join our team as the expert you are now and create your future.

Were seeking a Data Engineering Manager to join the Data Science & Machine Learning team in our Commercial Digital practice where youll lead the design development and delivery of data infrastructure that powers intelligent systems across Financial Services Manufacturing Energy & Utilities and other commercial industries.

Managers play a vibrant integral role at Huron. Their invaluable knowledge reflects in the projects they manage and the teams they lead. Known for building long-standing partnerships with clients they collaborate with colleagues to solve their most important challenges. Our Managers also spend significant time mentoring junior staff on the engagement teamsharing expertise feedback and encouragement. This promotes a culture of respect unity collaboration and personal achievement.

This isnt a maintenance role or a ticket queueyoull own the full data lifecycle from source integration through analytics-ready delivery while leading and developing a team of data engineers. Youll build systems that matter: real-time data architectures that feed mission-critical ML models transformation layers that turn messy enterprise data into trusted datasets and orchestration systems that ensure reliability at scale. Our clients are Fortune 500 companies looking for partners who can engineer and lead not just advise.

The variety is your first year you might lead a lakehouse implementation for a global manufacturers IoT data oversee a real-time streaming architecture for a financial services firms trading analytics and architect a data mesh strategy for a utility companys distribution systemsall while developing the next generation of data engineering talent at Huron. If you thrive on solving complex data challenges shipping production systems and building high-performing teams this role is for you.

What Youll Do

• Lead and mentor junior data engineersprovide technical guidance conduct code reviews and support professional development. Foster a culture of continuous learning and high-quality engineering practices within the team.
• Manage complex multi-workstream data engineering projectsoversee project planning resource allocation and delivery timelines. Ensure projects meet quality standards and client expectations while maintaining technical excellence.
• Design and architect end-to-end data solutionsfrom source extraction and ingestion through transformation quality validation and delivery. Make key technical decisions and own the overall data architecture.
• Lead development of modern data transformation layers using dbtimplementing modular SQL models testing frameworks documentation and CI/CD practices that ensure data quality and maintainability at scale.
• Architect lakehouse solutions using open table formats (Delta Lake Apache Iceberg) on Microsoft Fabric Snowflake and Databricksdesigning schemas optimizing performance and implementing governance frameworks.
• Establish DataOps best practicesdefine and implement CI/CD pipelines for data assets data quality monitoring observability lineage tracking and automated testing standards to ensure data infrastructure remains reliable in production.
• Serve as a trusted advisor to clientsbuild long-standing partnerships understand business problems translate data requirements into technical solutions and communicate architecture decisions to both technical and executive audiences.
• Contribute to business developmentparticipate in business development activities develop reusable assets and methodologies and help shape the technical direction of Hurons data engineering capabilities.

Required Qualifications

• 5 years of hands-on experience building and deploying data pipelines in productionnot just ad-hoc queries and exports. Youve built ETL/ELT systems that run reliably scale and are maintained over time.
• Experience leading and developing technical teamsincluding coaching mentorship code review and performance management. Demonstrated ability to build high-performing teams and develop junior talent.
• Strong SQL and Python programming skills with deep experience in PySpark for distributed data processing. SQL for analytics and data modeling; Python/PySpark for pipeline development and large-scale transformations.
• Experience building data pipelines that serve AI/ML systems including feature engineering workflows vector embeddings for retrieval-augmented generation (RAG) and data quality frameworks that ensure model reproducibility. Familiarity with emerging agent integration standards such as MCP (Model Context Protocol) and A2A (Agent-to-Agent) and the ability to design data services and APIs that can be discovered and consumed by autonomous AI agents.
• Experience with modern data transformation tools dbt particularly. You understand modular SQL development testing documentation practices and how to implement these at scale across teams.
• Experience with cloud data platforms and lakehouse architecturesSnowflake Databricks Microsoft Fabric and familiarity with open table formats (Delta Lake Apache Iceberg). Were platform-flexible but Microsoft-preferred.
• Proficiency with workflow orchestration tools such as Apache Airflow Dagster Prefect or Microsoft Data Factory. You understand DAGs scheduling dependency management and how to design reliable orchestration at scale.
• Solid foundation in data modeling concepts: dimensional modeling data vault normalization/denormalization and understanding of when different approaches are appropriate for different use cases.
• Excellent communication and client management skillsability to communicate technical concepts to non-technical stakeholders lead client meetings and build trusted relationships with executive audiences.
• Bachelors degree in Computer Science Engineering Mathematics or related technical field (or equivalent practical experience).
• Flexibility to work in a hybrid model with periodic travel to client sites as needed.

Preferred Qualifications

• Experience in Financial Services Manufacturing or Energy & Utilities industries.
• Background in building data infrastructure for ML/AI systemsfeature stores (Feast Databricks Feature Store) training data pipelines vector databases for RAG/LLM workloads or model serving architectures.
• Experience with real-time and streaming data architectures using Kafka Spark Streaming Flink or Azure Event Hubs including CDC patterns for data synchronization.
• Familiarity with MCP (Model Context Protocol) A2A (Agent-to-Agent) or similar standards for AI system data integration.
• Experience with data quality and observability frameworks such as Great Expectations Soda Monte Carlo or dbt tests at enterprise scale.
• Knowledge of data governance cataloging and lineage tools (Unity Catalog Purview Alation or similar).
• Experience with high-performance Python data tools such as Polars or DuckDB for efficient data processing.
• Cloud certifications (Snowflake SnowPro Databricks Data Engineer Azure Data Engineer or AWS Data Analytics).
• Consulting experience or demonstrated ability to work across multiple domains and adapt quickly to new problem spaces.
• Contributions to open-source data engineering projects or active participation in the dbt/data community.
• Masters degree or PhD in a technical field.

Why Huron

Variety that accelerates your growth. In consulting youll work across industries and data architectures that would take a decade to encounter at a single company. Our Commercial segment spans Financial Services Manufacturing Energy & Utilities and moreeach engagement is a new data ecosystem to master and a new platform to ship.

Impact you can measure. Our clients are Fortune 500 companies making significant investments in data infrastructure. The pipelines you build will power real decisionsthe ML models that drive production schedules the dashboards that inform pricing strategies the data products that enable self-service analytics. Youll see your work become the foundation others build on.

A team that builds. Hurons Data Science & Machine Learning team is a close-knit group of practitioners not just advisors. We write code build pipelines and deploy platforms. Youll work alongside engineers and data scientists who understand the craft and push each other to improve.

Investment in your development. We provide resources for continuous learning conference attendance and certification. As our DSML practice grows theres significant opportunity to take on technical leadership shape our capabilities and advance to senior leadership roles.

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