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Manager Data Engineering Jobs in Indiana (NOW HIRING)

Data Engineer

South Bend, IN · On-site

$112.20K - $134.80K/yr

Manage and optimize data storage solutions (data warehouses, lakes, lakehouses) * Implement ... data engineering or related roles * Strong SQL skills and experience working with relational ...

Data Engineer

South Bend, IN · On-site

$112.20K - $134.80K/yr

Manage and optimize data storage solutions (data warehouses, lakes, lakehouses) * Implement ... data engineering or related roles * Strong SQL skills and experience working with relational ...

Data Engineer

South Bend, IN · On-site

$112.20K - $134.80K/yr

Manage and optimize data storage solutions (data warehouses, lakes, lakehouses) * Implement ... data engineering or related roles * Strong SQL skills and experience working with relational ...

Data Strategy-Manager

Indianapolis, IN · On-site

$99K - $232K/yr

... Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified Professional - Alation Certified Data ...

Lead Data Engineer

Fort Wayne, IN · On-site

$113K - $135.70K/yr

This role combines hands-on engineering, architectural ownership, and leadership of contracted data ... Own and manage Petra, the organization's Microsoft Fabric-based data lakehouse. * Design, build ...

Data Engineer (in person)

Westfield, IN

$109.80K - $131.90K/yr

Our clients want us to apply the same engineering rigor we bring to software development to their ... Familiarity with orchestration and workflow management (Apache Airflow, Databricks Workflows ...

New

Data Engineer (in person)

Westfield, IN

$109.80K - $131.90K/yr

Our clients want us to apply the same engineering rigor we bring to software development to their ... Familiarity with orchestration and workflow management (Apache Airflow, Databricks Workflows ...

Data Engineer (in person)

Westfield, IN · On-site

$109.80K - $131.90K/yr

Our clients want us to apply the same engineering rigor we bring to software development to their ... Familiarity with orchestration and workflow management (Apache Airflow, Databricks Workflows ...

Technical Project Manager | About You As a Technical Project Manager, you are responsible for ... Collaborate with data engineering teams to clarify technical requirements and troubleshoot issues ...

Technical Project Manager | About You As a Technical Project Manager, you are responsible for ... Collaborate with data engineering teams to clarify technical requirements and troubleshoot issues ...

Technical Project Manager | About You As a Technical Project Manager, you are responsible for ... Collaborate with data engineering teams to clarify technical requirements and troubleshoot issues ...

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Showing results 1-20

Manager Data Engineering information

See Indiana salary details

$29.5K

$92.4K

$163.7K

How much do manager data engineering jobs pay per year?

As of May 29, 2026, the average yearly pay for manager data engineering in Indiana is $92,439.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,800.00 and $119,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Manager Data Engineering, and why are they important?

To thrive as a Manager Data Engineering, you need expertise in data architecture, advanced analytics, and leadership, typically supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop, Spark), data warehousing systems, cloud platforms (AWS, Azure), and certifications such as AWS Certified Data Analytics are highly valued. Strong communication, problem-solving, and team management skills help drive project success and foster collaboration. These skills ensure effective data solutions, alignment with business goals, and the ability to lead and grow high-performing engineering teams.

How does a Manager of Data Engineering typically collaborate with data scientists and business stakeholders?

A Manager of Data Engineering often serves as a bridge between technical teams and business stakeholders. They work closely with data scientists to ensure that data pipelines and infrastructure meet analytical needs, while also translating business requirements into actionable engineering solutions. Regular coordination meetings, clear documentation, and cross-functional projects are common, enabling seamless collaboration and alignment on goals. This role requires strong communication skills and the ability to balance technical priorities with business objectives.

What are Manager Data Engineering roles and responsibilities?

A Manager Data Engineering oversees teams that design, build, and maintain data infrastructure and pipelines for organizations. They are responsible for ensuring the efficient flow and storage of data, implementing best practices in data management, and collaborating with stakeholders to meet business data needs. Additionally, they mentor and guide data engineers, manage project timelines, and ensure data security and quality standards are met. Their role often involves strategic planning to enable data-driven decision making across the company.

What is the difference between Manager Data Engineering vs Data Engineer?

AspectManager Data EngineeringData Engineer
Required CredentialsBachelor's or Master's in CS, Data Science, or related; often leadership experienceBachelor's or higher in CS, IT, or related; technical certifications optional
Work EnvironmentTeam leadership, project management, strategic planningData pipeline development, coding, data modeling
Employer & Industry UsageTech companies, finance, healthcare, where data teams are commonData-focused roles across various industries

The main difference is that Manager Data Engineering oversees data teams and projects, focusing on strategy and leadership, while Data Engineers handle the technical implementation of data pipelines and infrastructure. Managers typically have more experience and leadership skills, whereas Data Engineers are more hands-on with coding and data architecture.

What are the most commonly searched types of Data Engineering jobs in Indiana? The most popular types of Data Engineering jobs in Indiana are:
What are popular job titles related to Manager Data Engineering jobs in Indiana? For Manager Data Engineering jobs in Indiana, the most frequently searched job titles are:
Infographic showing various Manager Data Engineering job openings in Indiana as of May 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $92,439 per year, or $44.4 per hour.
Enterprise Data Architect

Full-time

Posted 14 days ago


Steel Dynamics rating

7.8

Company rating: 7.8 out of 10

Based on 57 frontline employees who took The Breakroom Quiz

161st of 511 rated manufacturers


Job description

Steel Dynamics

The Enterprise Data Architect is the technical cornerstone of Steel Dynamics' enterprise data platform initiative. This newly created role will lead the design and build-out of a company-wide data platform that will serve as SDI's first foundation for enterprise reporting, analytics, and AI/ML.

SDI is a highly decentralized organization. Divisions own their source systems and operate with significant autonomy. The Enterprise Data Architect must be equally comfortable working independently to drive the architecture forward and collaboratively to bring divisions along. The role requires earning trust across divisions rather than relying on positional authority.

This role begins as a senior individual contributor with significant build-out responsibility, and is expected to evolve as the platform matures and the enterprise data function grows. The strongest candidates will be excellent as both architects and builders.

What Makes This Role Distinctive

  • Greenfield enterprise platform with growth trajectory. This is a build-from-the-ground-up opportunity. Architectural choices made in this role will shape SDI's data foundation for the next decade, and the role is structured to evolve as the platform matures and the enterprise data function grows.
  • Real architectural authority. SDI has not locked in technology commitments for this platform. The Enterprise Data Architect's recommendations on platform, tooling, and standards will drive the decisions.
  • Builder-leader trajectory. This role is positioned to play a central part in shaping and growing SDI's enterprise data engineering capability over time.
  • A culture that moves fast when aligned. SDI is decentralized, but when we align, we move with surprising speed. A successful architect here will see their designs translated into operating reality faster than in most enterprise environments.

About Steel Dynamics, Inc.

Steel Dynamics is one of the largest domestic steel producers and metals recyclers in North America, with approximately 15,000 employees and operations spanning steelmaking, steel fabrication, metals recycling, aluminum, and biocarbon. SDI's culture is built on entrepreneurial spirit, decentralized decision-making, accountability, and aligned long-term interests across all stakeholders. We are committed to safety, operational excellence, and continuous innovation.


  • Lead the design and build-out of the enterprise data platform, including platform selection, reference architecture, and the standards and patterns the platform will operate on.
  • Define the architecture for moving data from divisional source systems — predominantly on-premises SQL Server — into the cloud-hosted platform, including ingestion, security, and reliability.
  • Establish enterprise data engineering standards governing the corporate-owned platform.
  • Partner with divisional IT teams on integrating division data into the platform, providing architectural guidance and technical support without taking ownership of divisional data away from the divisions.
  • Provide hands-on data engineering support to divisions that do not yet have dedicated data engineering capability; transition this work to a growing team as the function scales.
  • Design the security, governance, and access-control model for the platform.
  • Architect the platform to support enterprise AI and machine learning workloads.
  • Define environment, CI/CD, cost management, and operational monitoring approaches for the platform.
  • Serve as the senior technical voice in vendor evaluations, proof-of-concept work, and platform decisions.
  • Mentor divisional data engineers and analysts working within the platform.
  • Communicate clearly with non-technical executive stakeholders, translating architectural choices into business outcomes, risks, and trade-offs.

Required

  • 10+ years of progressive experience implementing large-scale software systems in production enterprise environments.
  • 5+ years experience in data engineering, data warehousing, and/or data architecture in production environments.
  • Demonstrated experience leading and personally owning the design and delivery of at least one greenfield or major-overhaul enterprise data platform spanning multiple business units, source systems, or geographies.
  • Demonstrated experience designing hybrid cloud / on-premises data architectures, including secure and reliable movement of data from on-premises source systems into cloud platforms.
  • Working proficiency across multiple cloud data platforms sufficient to lead a credible platform evaluation and make defensible recommendations.
  • Strong familiarity with the Microsoft data and analytics ecosystem.
  • Strong technical foundation across SQL, a general-purpose programming language used in data engineering, modern data engineering practices, and data warehousing fundamentals.
  • Experience integrating data from heterogeneous source systems in a multi-business-unit environment, including ERP and operational systems.
  • Working knowledge of data security, governance, and compliance frameworks sufficient to architect compliant data platforms.
  • Excellent written and verbal communication skills, with proven ability to present architectural concepts and trade-offs to both technical teams and non-technical executive stakeholders.
  • Demonstrated ability to work effectively in a decentralized organizational structure — building consensus, earning trust, and driving outcomes through influence rather than authority.
  • Bachelor's degree in a relevant field, or equivalent professional experience.

Preferred

  • Experience designing data platforms in manufacturing, metals, industrial, or other heavy-asset industries.
  • Experience integrating MES, historian, and shop-floor data alongside ERP and financial data.
  • Experience architecting data platforms that support AI/ML and large language model workloads.
  • Experience leading or mentoring distributed data engineering teams.
  • Experience establishing data governance practices in decentralized, multi-business-unit organizations.

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


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About Steel Dynamics

Sourced by ZipRecruiter

Steel Dynamics is one of the largest and most diversified domestic steel producers and metals recyclers in the United States, with an estimated steelmaking and coating capacity of approximately 13 million tons, and facilities located throughout the United States and in Mexico. We operate using a circular manufacturing model, producing lower-carbon-emission, quality steel using electric arc furnace (EAF) technology with recycled ferrous scrap as the primary input. Our circular economy is powered by our three primary operating platforms: steel, metals recycling, and steel fabrication. Our steel operations produce steel products, including hot roll, cold roll, and coated sheet steel, structural steel beams and shapes, rail, engineered special-bar-quality steel, cold finished steel, merchant bar products, and specialty steel sections. Our metals recycling operations collect and process ferrous and nonferrous scrap from manufacturing and end-of-life items, such as automobiles, appliances, and machinery. This processed scrap is then sold to end-users for reuse, including our EAF steel mills, which produce new steel from the scrapped material. We sell a meaningful amount of steel to our own steel fabrication operations that in turn produce and sell structural steel joist and deck building systems to consumers.

Industry

Manufacturing

Company size

5,001 - 10,000 Employees

Headquarters location

Fort Wayne, IN, US

Year founded

1993