Data Jobs in Columbus, IN

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Data Engineer Principal

Cummins Inc. Columbus, IN

Columbus, IN

Today

$131k - $160k/yr Full time Manager Analytics Big Data

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Job Description

As a Principal Data Engineer at Cummins in Columbus, Indiana, you will lead the strategy and evolution of enterprise data platforms that support scalable analytics, AI, and business intelligence. The role emphasizes resilient pipeline delivery, strong governance, and technical leadership across complex enterprise environments.

Role Overview

You will be responsible for the architecture and continuous advancement of enterprise data platforms enabling trusted, high-quality data assets. This includes guiding the integration and delivery of data from diverse systems to support executive and business-critical decision making.

Responsibilities

Lead the strategy, architecture, and evolution of enterprise data platforms for analytics, AI, and business intelligence solutions.
Partner with business leaders, product teams, and technical stakeholders to translate complex requirements into high-value data solutions.
Design and optimize data lake, lakehouse, data warehouse, and cloud-based architectures to improve accessibility, quality, and performance.
Deliver resilient and reusable data pipelines to accelerate decision-making and reduce time-to-insight.
Champion data governance, security, compliance, and quality standards to ensure trusted and reliable enterprise data assets.
Drive continuous improvement initiatives that enhance scalability, operational efficiency, cost optimization, and platform performance.
Provide technical leadership, mentoring, and architectural guidance to data engineering teams while fostering engineering excellence.
Enable executive and business-critical decisions through the integration and delivery of data from diverse enterprise systems.

Required Experience and Qualifications

Proven ability to architect and deliver enterprise-scale data platforms, data models, and cloud-based analytics solutions that support business growth and innovation.
Deep expertise in modern data engineering practices, including scalable pipeline development, data integration, data modeling, distributed processing, and cloud-native architectures.
Strong leadership and stakeholder management skills, with the ability to influence cross-functional teams and align solutions with business outcomes.
Advanced knowledge of data governance, security, compliance, and modern software engineering practices, including Agile, DevSecOps, CI/CD, and automation.
10+ years of progressive experience in data engineering, data architecture, analytics engineering, or a closely related technical field, including leading complex enterprise data solutions.
Experience delivering enterprise data, analytics, or AI solutions in large, complex manufacturing and supply-chain environments, across areas such as planning, procurement, manufacturing, inventory, logistics, engineering, aftermarket, commercial, finance, or related operational functions.
Ability to work directly with business stakeholders to clarify requirements, explore available data, and develop prototypes or proof-of-concepts before scaling to production.
Hands-on expertise in modern data engineering, including SQL, Python/PySpark, data modeling, scalable pipeline design, data integration, and distributed/cloud data platforms.
Demonstrated experience designing, building, and operating batch and streaming or near-real-time data pipelines, including orchestration, reliability, monitoring, recovery, scalability, and performance.
Experience integrating data from enterprise source systems such as ERP, operational systems, legacy applications and databases, APIs, cloud platforms, event streams, IoT/telemetry sources, and structured or unstructured data.
Demonstrated experience designing and evolving data lake, lakehouse, data warehouse, or comparable modern analytical platforms.
Strong data modeling experience across relational, dimensional, and enterprise/domain data modeling, including fact and dimension structures and star or snowflake schemas.
Experience building reusable data engineering frameworks, shared data foundations, enterprise data models, and governed data products to support multiple use cases.
Strong experience with enterprise data platforms such as Databricks, Snowflake, Azure data services, or comparable cloud/data technologies.
Proven ability to lead end-to-end solutions from discovery and requirements definition through architecture, implementation, production deployment, monitoring, optimization, and support.
Demonstrated ability to operate in complex, ambiguous data environments involving evolving requirements, integration constraints, and data-quality issues.
Strong collaboration across Business, Data Science, AI Engineering, Analytics, Enterprise Architecture, and platform/application teams.
Experience providing technical leadership, including architecture guidance, design reviews, engineering standards, and mentoring.
Understanding of data engineering and architecture foundations needed to support advanced analytics, machine learning, GenAI, and other AI-enabled solutions while maintaining quality, governance, security, scalability, reuse, performance, and cost standards.

Technologies

SQL
Python, PySpark
Agile, DevSecOps, CI/CD
Data lake, Lakehouse, Data warehouse
Databricks, Snowflake
Azure data services
ERP, APIs, Event streams
IoT/telemetry sources
Batch and streaming data pipelines; near-real-time data pipelines
Streaming
Distributed processing
Cloud-native architectures

Education and Licensing

College, university, or equivalent degree in a relevant technical discipline, or relevant equivalent experience, required.
This position may require licensing for compliance with export controls or sanctions regulations.

Additional Responsibilities and Preferred Competencies

Experience designing enterprise-level analytical, operational, or domain data models across multiple manufacturing and supply-chain functions and source systems.
Experience implementing metadata-driven pipelines, reusable ingestion frameworks, self-service data capabilities, data governance, lineage, observability, or reusable data-product patterns.
Experience with data architecture and engineering patterns supporting GenAI and RAG solutions, including document ingestion and processing, embeddings, vector search/vector databases, semantic models, knowledge graphs, ontologies, or retrieval pipelines.
Experience working with manufacturing and supply-chain technologies and data sources such as ERP/MRP, MES, PLM, WMS, TMS, planning systems, engineering systems, and IoT/connected-product platforms.
Ability to balance near-term delivery with long-term architecture, scalability, reuse, governance, cost optimization, and technical debt.
Relevant Databricks, Snowflake, Azure, AWS, GCP, or comparable data-platform certifications are a plus; demonstrated production experience and technical depth are valued more strongly than certification alone.

Location, Job Type, and Employment Details

Location: Columbus, IN (on-site)
Role category: On-site with flexibility
Job type: Exempt - Experienced
On-site indicator: 100% ON-SITE: No
ReqID: 2438266

Compensation

Salary range: USD 131,220 - 160,380 per year
Minimum salary: $131,220
Maximum salary: $160,380

Salary range estimate note: The salary range provided is a good faith estimate on the applicable range. Final salary offer will be determined after considering relevant factors, including qualifications and experience, where appropriate.

Relocation

Relocation package: Yes

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