Data Engineering Manager in Belfast

Lead and mentor junior data engineers—provide 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 projects—oversee 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 solutions—from 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 dbt—implementing 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 Databricks—designing schemas, optimizing performance, and implementing governance frameworks.

Establish DataOps best practices—define 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 clients—build 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 development—participate in business development activities, develop reusable assets and methodologies, and help shape the technical direction of Huron's data engineering capabilities.

5+ years of hands-on experience building and deploying data pipelines in production—not just ad-hoc queries and exports. You've built ETL/ELT systems that run reliably, scale, and are maintained over time.

Experience leading and developing technical teams—including 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 architectures—Snowflake, Databricks, Microsoft Fabric, and familiarity with open table formats (Delta Lake, Apache Iceberg). We're 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 skills—ability to communicate technical concepts to non-technical stakeholders, lead client meetings, and build trusted relationships with executive audiences.

Bachelor's 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.

Experience in Financial Services, Manufacturing, or Energy & Utilities industries.

Background in building data infrastructure for ML/AI systems—feature 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.

Master's degree or PhD in a technical field.

At Huron, we’re redefining what a consulting organization can be. We go beyond advice to deliver results that last. We inherit our client’s challenges as if they were our own. We help them transform for the future. We advocate. We make a difference. And we intelligently, passionately, relentlessly do great work…together.

Whether you have years of experience or come right out of college, we invite you to explore our many opportunities. Find out how you can use your talents and develop your skills to make an impact immediately. Learn about how our culture and values provide you with the kind of environment that invites new ideas and innovation. Come see how we collaborate with each other in a culture of learning, coaching, diversity and inclusion. And hear about our unwavering commitment to make a difference in partnership with our clients, shareholders, communities and colleagues.

Huron Consulting Group offers a competitive compensation and benefits package including medical, dental, and vision coverage to employees and dependents; a 401(k) plan with a generous employer match; an employee stock purchase plan; a generous Paid Time Off policy; and paid parental leave and adoption assistance. Our Wellness Program supports employee total well-being by providing free annual health screenings and coaching, bank at work, and on-site workshops, as well as ongoing programs recognizing major events in the lives of our employees throughout the year. All benefits and programs are subject to applicable eligibility requirements.

Huron is fully committed to providing equal employment opportunity to job applicants and employees in recruitment, hiring, employment, compensation, benefits, promotions, transfers, training, and all other terms and conditions of employment. Huron will not discriminate on the basis of age, race, color, gender, marital status, sexual orientation, gender identity, pregnancy, national origin, religion, veteran status, physical or mental disability, genetic information, creed, citizenship or any other status protected by laws or regulations in the locations where we do business. We endeavor to maintain a drug-free workplace.