Data Engineer at STEEL WAREHOUSE CO LLC

South Bend, Indiana, United States -

Full Time

Start Date

Immediate

Expiry Date

25 Jun, 26

Salary

0.0

Posted On

27 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, ETL/ELT, Python, Spark, Cloud Platforms, Azure, AWS, GCP, Snowflake, BigQuery, Redshift, Fabric, Data Modeling, Data Governance, Airflow, DevOps

Industry

Primary Metal Manufacturing

Description

Description We are seeking a Data Engineer to design, build, and maintain scalable data pipelines and infrastructure that support analytics, reporting, and data-driven decision making. This role will also play a key part in establishing and enforcing data governance standards to ensure data is accurate, secure, and trusted across the organization. Key Responsibilities Design, develop, and maintain robust ETL/ELT pipelines to ingest, transform, and load data from various sources Build and optimize data models to support analytics and reporting use cases Ensure data quality, integrity, and reliability through monitoring, validation, and testing Implement and support data governance practices, including data lineage, cataloging, and metadata management Enforce data standards, naming conventions, and access controls across datasets Partner with business stakeholders to define data ownership, definitions, and quality expectations Manage and optimize data storage solutions (data warehouses, lakes, lakehouses) Implement performance tuning and cost optimization strategies Maintain documentation for data architecture, pipelines, and governance processes Support deployment and orchestration of data workflows using modern tools Troubleshoot and resolve data issues in a timely manner Requirements Bachelor’s degree in Computer Science, Information Systems, or related field (or equivalent experience) 2–5+ years of experience in data engineering or related roles Strong SQL skills and experience working with relational databases Experience building data pipelines using tools such as Python, Spark, or similar Familiarity with cloud platforms (Azure, AWS, or GCP) Experience with data warehousing technologies (e.g., Snowflake, BigQuery, Redshift, or Fabric) Understanding of data modeling concepts (star schema, normalization, etc.) Experience supporting or working within data governance frameworks (data quality, lineage, access control, or catalog tools) Preferred Qualifications: Experience with orchestration tools (Airflow, Azure Data Factory, etc.) Knowledge of real-time/streaming data processing Familiarity with DevOps practices (CI/CD, version control) Experience working in a lakehouse architecture (e.g., Delta Lake, Microsoft Fabric) Experience with data governance tools (e.g., Microsoft Purview, Collibra, Alation) Strong understanding of data security and compliance best practices Strong problem-solving and communication skills

Responsibilities

The Data Engineer will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support analytics and data-driven decision-making. This includes developing robust ETL/ELT processes, ensuring data quality, and establishing data governance standards across the organization.