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Data Engineer - Copperworks

Data Engineer - Copperworks

Steel Dynamics, IncNew Haven, IN, US
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Overview

The Data Engineer at Copperworks will own and evolve our modern data stack, moving data from diverse sources into trusted, analytics-ready models that power decision-making across the business. You’ll design and operate pipelines in Dagster, model with dbt, shape semantic models in Power BI / Fabric, and optimize and manage our Azure stack (Azure SQL Database, Azure Data Lake, Azure Data Factory, . This role will eventually involve migrating from our hybrid infrastructure to a more cloud-centric setup leveraging more of the Fabric platform.

Responsibilities

Duties and responsibilities include, but are not limited to :

  • Design, build, and maintain ELT pipelines in Dagster / Python with robust scheduling, observability, and alerting.
  • Develop modular, tested data models in dbt (sources, staging, marts), including incremental strategies and documentation.
  • Implement performant transformations using T-SQL and DuckDB (or Spark SQL equivalents) for analytics at scale.
  • Ingest and orchestrate data flows with Azure Data Factory and Azure Data Lake; manage datasets, and cost / performance.
  • Build and maintain Power BI semantic models (star schemas, relationships, calculation groups / measures), optimizing for refresh and query performance
  • Leverage Microsoft Fabric for end-to-end analytics workflows, governance, and distribution.
  • Manage integrations with external APIs / applications such as our Process AI platform and Salesforce CRM
  • Administer and optimize Azure SQL / On-Prem SQL Server objects (views, sprocs, triggers, indexes), ensuring data quality and reliability.
  • Manage code in Linux / Bash (WSL Ubuntu) environments for our on-premise data server.
  • Partner with end users and business stakeholders to gather requirements, perform testing and QA, and ensure a smooth handoff of deliverables.
  • Monitor, troubleshoot, and continuously improve pipeline reliability, cost, and performance.

Qualifications

Required

  • 3–5 years of professional data engineering experience in a production environment.
  • Hands-on with orchestration tools (Dagster preferred; Airflow / Prefect acceptable).
  • Proficiency with a modeling framework like dbt or sqlmesh (tests, snapshots, macros).
  • Intermediate Python (data access, transformations, packaging / venv, type-safe code, unit tests).
  • SQL expertise (advanced T-SQL) : window functions, performance tuning, query plans, indexing strategies.
  • Experience with Spark SQL or similar query engines; strong comfort with DuckDB (or willingness to ramp quickly).
  • Azure : Data Lake (ADLS Gen2) and Data Factory for ingestion / orchestration.
  • Working knowledge of Microsoft Fabric and Power BI semantic modeling (dimensional design, DAX measures).
  • Linux / Bash skills; ability to work in WSL Ubuntu.
  • API / application integrations experience (REST / JSON, OAuth2 / keys, Odata).
  • Version control with Git and collaborative workflows (PRs, code reviews).
  • Strong communication, documentation, and stakeholder partnership skills.

    • Preferred

  • Experience with Dynamics 365 Finance & Operations (D365 F&O) data models and integration patterns.
  • Data warehousing best practices (star schemas, SCDs, incremental strategies, CDC).
  • Power BI performance tuning (aggregations, incremental refresh, understanding of different storage modes).
  • Azure access control (IAM) and application management in Azure.

    • Steel Dynamics, Inc., and all affiliated entities are equal opportunity employers.

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    Data Engineer • New Haven, IN, US