Huron
Huron
Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation, and navigate constant change. We're seeking a Data Engineering Manager to join the Data Science & Machine Learning team in our Commercial Digital practice, where you'll lead the design, development, and delivery of data infrastructure that powers intelligent systems across Financial Services, Manufacturing, Energy & Utilities, and other commercial industries. What You’ll Do
Lead and mentor junior data engineers —provide technical guidance, conduct code reviews, and support professional development. Manage complex multi-workstream data engineering projects —oversee project planning, resource allocation, and delivery timelines. Design and architect end-to-end data solutions —from source extraction and ingestion through transformation, quality validation, and delivery. Lead development of modern data transformation layers using dbt —implementing modular SQL models, testing frameworks, documentation, and CI/CD practices. Architect lakehouse solutions using open table formats
(Delta Lake, Apache Iceberg) on Microsoft Fabric, Snowflake, and Databricks. Establish DataOps best practices —define and implement CI/CD pipelines for data assets, data quality monitoring, observability, lineage tracking, and automated testing standards. Serve as a trusted advisor to clients —build long-standing partnerships, translate data requirements into technical solutions, and communicate architecture decisions. Contribute to business development —participate in business development activities and shape the technical direction of Huron's data engineering capabilities. Required Qualifications
5+ years of hands‑on experience building and deploying data pipelines in production . Experience leading and developing technical teams —coaching, mentorship, code review, and performance management. Strong SQL and Python programming skills —deep experience in PySpark for distributed data processing. Experience building data pipelines that serve AI/ML systems —feature engineering workflows, vector embeddings, and data quality frameworks. Experience with modern data transformation tools, especially dbt . Experience with cloud data platforms and lakehouse architectures —Snowflake, Databricks, Microsoft Fabric, Delta Lake, Apache Iceberg. Proficiency with workflow orchestration tools —Airflow, Dagster, Prefect, or Microsoft Data Factory. Solid foundation in data modeling concepts —dimensional modeling, data vault, normalization/denormalization. Excellent communication and client management skills . Bachelor's degree in Computer Science, Engineering, Mathematics, or related field . Willingness to travel approximately 30%
to client sites as needed. Preferred Qualifications
Experience in Financial Services, Manufacturing, or Energy & Utilities industries. Background in building data infrastructure for ML/AI systems—feature stores, training data pipelines, vector databases, or model serving architectures. Experience with real‑time and streaming data architectures using Kafka, Spark Streaming, Flink, or Azure Event Hubs. Familiarity with MCP (Model Context Protocol), A2A (Agent-to-Agent), or similar standards. 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. Experience with high-performance Python data tools such as Polars or DuckDB. Cloud certifications (Snowflake SnowPro, Databricks Data Engineer, Azure Data Engineer, or AWS Data Analytics). Consulting experience or demonstrated ability to work across multiple domains. Contributions to open-source data engineering projects or active participation in the dbt/data community. Master's degree or PhD in a technical field. Why Huron
Variety that accelerates your growth.
In consulting, you'll work across industries and data architectures that would take a decade to encounter at a single company. Impact you can measure.
The pipelines you build will power real decisions, the ML models that drive production schedules, and the dashboards that inform pricing strategies. A team that builds.
Huron's Data Science & Machine Learning team is a close-knit group of practitioners, not just advisors. You’ll 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, there's significant opportunity to take on technical leadership and advance to senior leadership roles. Position Level: Manager Country: United States of America
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Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation, and navigate constant change. We're seeking a Data Engineering Manager to join the Data Science & Machine Learning team in our Commercial Digital practice, where you'll lead the design, development, and delivery of data infrastructure that powers intelligent systems across Financial Services, Manufacturing, Energy & Utilities, and other commercial industries. What You’ll Do
Lead and mentor junior data engineers —provide technical guidance, conduct code reviews, and support professional development. Manage complex multi-workstream data engineering projects —oversee project planning, resource allocation, and delivery timelines. Design and architect end-to-end data solutions —from source extraction and ingestion through transformation, quality validation, and delivery. Lead development of modern data transformation layers using dbt —implementing modular SQL models, testing frameworks, documentation, and CI/CD practices. Architect lakehouse solutions using open table formats
(Delta Lake, Apache Iceberg) on Microsoft Fabric, Snowflake, and Databricks. Establish DataOps best practices —define and implement CI/CD pipelines for data assets, data quality monitoring, observability, lineage tracking, and automated testing standards. Serve as a trusted advisor to clients —build long-standing partnerships, translate data requirements into technical solutions, and communicate architecture decisions. Contribute to business development —participate in business development activities and shape the technical direction of Huron's data engineering capabilities. Required Qualifications
5+ years of hands‑on experience building and deploying data pipelines in production . Experience leading and developing technical teams —coaching, mentorship, code review, and performance management. Strong SQL and Python programming skills —deep experience in PySpark for distributed data processing. Experience building data pipelines that serve AI/ML systems —feature engineering workflows, vector embeddings, and data quality frameworks. Experience with modern data transformation tools, especially dbt . Experience with cloud data platforms and lakehouse architectures —Snowflake, Databricks, Microsoft Fabric, Delta Lake, Apache Iceberg. Proficiency with workflow orchestration tools —Airflow, Dagster, Prefect, or Microsoft Data Factory. Solid foundation in data modeling concepts —dimensional modeling, data vault, normalization/denormalization. Excellent communication and client management skills . Bachelor's degree in Computer Science, Engineering, Mathematics, or related field . Willingness to travel approximately 30%
to client sites as needed. Preferred Qualifications
Experience in Financial Services, Manufacturing, or Energy & Utilities industries. Background in building data infrastructure for ML/AI systems—feature stores, training data pipelines, vector databases, or model serving architectures. Experience with real‑time and streaming data architectures using Kafka, Spark Streaming, Flink, or Azure Event Hubs. Familiarity with MCP (Model Context Protocol), A2A (Agent-to-Agent), or similar standards. 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. Experience with high-performance Python data tools such as Polars or DuckDB. Cloud certifications (Snowflake SnowPro, Databricks Data Engineer, Azure Data Engineer, or AWS Data Analytics). Consulting experience or demonstrated ability to work across multiple domains. Contributions to open-source data engineering projects or active participation in the dbt/data community. Master's degree or PhD in a technical field. Why Huron
Variety that accelerates your growth.
In consulting, you'll work across industries and data architectures that would take a decade to encounter at a single company. Impact you can measure.
The pipelines you build will power real decisions, the ML models that drive production schedules, and the dashboards that inform pricing strategies. A team that builds.
Huron's Data Science & Machine Learning team is a close-knit group of practitioners, not just advisors. You’ll 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, there's significant opportunity to take on technical leadership and advance to senior leadership roles. Position Level: Manager Country: United States of America
#J-18808-Ljbffr