Data Engineer

STEEL WAREHOUSE CO LLCSouth Bend, IN
2h

About The Position

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.

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)

Nice To Haves

  • 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

  • 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
© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service