Data Engineering Manager
First seen by Alion on Sep 4, 2026.
Basic Job Functions :
This position leads the strategy, design, development, implementation, and optimization of enterprise data platforms and data products across the organization, while building and leading a team of data engineers. Works closely with senior business stakeholders, analytics leadership, data science teams, IT teams, and enterprise architects to define enterprise data strategy and resolve the most complex, high-impact business problems through scalable data engineering solutions.
Applies expert-level knowledge of data architecture, cloud technologies, data modeling, ETL/ELT frameworks, streaming systems, and distributed computing to build highly reliable, secure, and cost-efficient data pipelines at enterprise scale. Owns the strategic roadmap and drives the design, development, deployment, monitoring, and optimization of enterprise-grade data platforms that enable analytics, machine learning, reporting, and operational decision-making across the organization.
Serves as a senior technical leader and people manager within the unit, providing strategic direction, oversight, mentorship, and guidance on data engineering best practices, architecture standards, platform governance, and implementation approaches. Manages, coaches, and develops a team of data engineers, owning hiring, performance management, career development, and training. Communicates technical solutions, architecture strategy, and team performance to senior management and business partners across departments. Leads platform modernization and the adoption of emerging technologies across multiple sites and functions.
Education/Experience :
- Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Engineering, Electrical Engineering, Applied Mathematics, or related technical discipline with 9+ years of relevant experience in Data Engineering, Data Platform Development, Cloud Engineering, or Big Data Solutions, including 2+ years in a technical leadership or people management capacity.
- Master's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or related technical field with 7+ years of relevant experience in Data Engineering, Data Platform Development, Cloud Engineering, or Big Data Solutions, including 2+ years in a technical leadership or people management capacity.
- PhD degree in Computer Science, Data Engineering, Information Systems, or related field with 5+ years of relevant experience in Data Engineering, Cloud Data Platforms, Distributed Computing, or Advanced Data Management Solutions, including 2+ years in technical leadership or people management capacity.
Required Skills :
- Expert-level command of advanced SQL development, query optimization, database design, indexing strategies, performance tuning, and relational database management systems.
- Expert-level experience with cloud platforms such as Microsoft Fabric, Azure, Google Cloud Platform, Databricks or AWS.
- Expert-level experience with Infrastructure as Code (IaC) technologies such as Terraform, ARM Templates, CloudFormation.
- Expert-level experience with containerization and orchestration technologies including Docker, Kubernetes, OpenShift.
- Expert-level experience architecting, developing, and maintaining scalable ETL/ELT pipelines using tools such as Fabric Data Factory, Azure Data Factory, Databricks, Dataflow, Apache Spark, Apache Airflow.
- Expert-level experience with modern data lake architecture, Lakehouse platforms, Medallion Architecture, Delta Lake, Parquet.
- Expert-level experience with batch and real-time/streaming ingestion frameworks including Kafka, NiFi, Azure Event Hub, Kinesis, Spark Streaming, Flink.
- Expert-level experience in data modeling techniques including dimensional modeling, star schema, snowflake schema, and Data Vault methodologies.
- Expert-level experience with API integrations, REST services, GraphQL, data exchange protocols, webhooks.
- Expert-level command of Linux environments, shell scripting, automation, process monitoring.
- Expert-level experience with Git, GitHub, GitLab, Azure DevOps, CI/CD pipelines, DevSecOps practices.
- Expert-level proficiency in Python, Scala, Java, or similar programming languages.
- Expert-level experience with big data technologies such as Hadoop, Spark, Hive, Delta Lake, Iceberg, HBase.
- Advanced knowledge of data governance, data quality management, metadata management, data lineage, master data management.
- Advanced understanding of data security principles, encryption, role-based access controls, identity management.
Essential Responsibilities :
- Directs the design and implementation of enterprise-scale data platforms, data lakehouses, and cloud-native architectures.
- Directs the design, development, and maintenance of complex, enterprise-scale batch and streaming ingestion pipelines.
- Owns conceptual, logical, and physical data models supporting enterprise business processes.
- Owns the design and management of cloud infrastructure supporting enterprise data platforms.
- Establishes enterprise-wide data quality controls, validations, and monitoring frameworks.
- Serves as the senior data engineering subject matter expert and technical authority for the organization.
- Leads large and complex data engineering projects and major components of enterprise business initiatives.
- Directs the build-out of CI/CD pipelines supporting automated testing and deployment processes.
- Manages, mentors, and develops a team of data engineers, acting as their direct people manager.
- Researches and maintains deep awareness of emerging technologies, cloud services, and industry best practices.
Reporting Relationships :
- This position reports to the Sr. Manager - Data Science IND.
- This position has direct reports and should manage leads and engineers across one or more teams or sites.
Travel :
- Domestic and international travel may be required.
Skills
Data Engineering, Engineering Management, Big Data, Data Management, Microsoft Fabric, SQL, ETL, Azure Data Factory, Azure Databricks, Apache Airflow, DataLake