Data Engineer

Williams International•Pontiac, MI

2d•Onsite

About The Position

Williams International is seeking a Data Engineer to develop and support data engineering projects, providing technical expertise and guidance across the organization and specialized technical input to assigned departments. The role is 100% on-site and requires U.S. citizenship. The Data Engineer will build and maintain enterprise data systems and platforms, including ontologies, data catalogs, metadata systems, ingestion pipelines, data lakes, warehouses, and lakehouses. The position also establishes data quality, governance, lineage, security, and compliance practices; manages data platform tooling and pipeline delivery; and collaborates with teams across software, engineering, analytics, business, IT, and database administration. The role requires a bachelor’s degree in a relevant field and at least four years of hands-on experience with enterprise data systems. The successful candidate will have experience with data pipelines and ETL/ELT, data storage and modeling, SQL, data governance, cloud data environments, enterprise integrations, version control, agile practices, and containerization or orchestration technologies. U.S. citizenship is required, and the position may require eligibility to obtain a U.S. Government Security Clearance.

Requirements

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
At least 4 years of hands-on experience working with enterprise data systems.
Experience designing and maintaining batch and/or streaming data ingestion pipelines.
Experience building and optimizing ETL/ELT workflows.
Experience with relational and nonrelational databases, data lakes, warehouses, and lakehouse architectures.
Ability to write performant SQL and develop data models.
Experience managing data quality, validation, lineage, and governance processes.
Experience developing and maintaining ontologies, taxonomies, and semantic data models for enterprise data consistency and discoverability.
Proficiency in Python, C#, and SQL, including production-grade data processing code.
Experience with cloud data environments such as Azure, AWS, or GCP, including storage, compute, networking, and orchestration services used for data pipelines.
Familiarity with enterprise systems and integration tools such as ERP, MES, PLM, or API-based data exchange.
Experience with version control systems such as Git or Bitbucket and agile development practices.
Experience with containerization or orchestration technologies such as Docker or Kubernetes to operationalize or scale data workloads.
Strong analytical skills and ability to work independently to identify and solve complex problems.
U.S. citizenship is required.
Ability to obtain a U.S. Government Security Clearance if needed; selected candidates may be subject to a government security investigation and must meet eligibility requirements for access to classified information.

Responsibilities

Build and maintain enterprise ontologies, data catalogs, and metadata systems.
Design and implement scalable batch and streaming ingestion pipelines.
Develop and optimize data lake, warehouse, and lakehouse environments.
Create robust data models and curated, high-quality datasets.
Establish and maintain data quality, validation, lineage, and governance standards.
Implement security, compliance, and policy controls for data assets in alignment with cybersecurity requirements.
Optimize pipeline performance, reliability, cost, and observability.
Manage data platform tooling, infrastructure-as-code, and CI/CD for pipelines.
Work with DBAs to design and optimize database schemas, configure database settings, and ensure data availability and reliability.
Assist with query optimization and data systems troubleshooting.
Collaborate with software, engineering, analytics, business, and IT teams.
Document pipelines, datasets, and best practices for enterprise data systems.
Provide technical expertise and guidance across the organization and specialized technical input to assigned departments.