Engineer 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

Columbus, Indiana (Onsite) role at Cummins Inc. leading the strategy, architecture, and evolution of enterprise data platforms. This position focuses on enabling scalable analytics, AI, and business intelligence through resilient data pipelines supported by strong governance, security, compliance, and quality standards.

Compensation: USD 131,220 - 160,380 per year.
Role type: Exempt - Experienced. On-site with flexibility.
Relocation package: Yes.

What you will do

Lead the strategy, architecture, and evolution of enterprise data platforms that support scalable analytics, AI, and business intelligence outcomes.
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 that accelerate decision-making and reduce time-to-insight.
Champion data governance, security, compliance, and quality standards for trusted enterprise data assets.
Drive continuous improvement to 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 integration and delivery of data from diverse enterprise systems.

What you bring

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, including scalable pipeline development, data integration, data modeling, distributed processing, and cloud-native architectures.
Strong leadership and stakeholder management skills to influence cross-functional teams, navigate ambiguity, and align technical solutions to 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 field, including leading complex enterprise data solutions.
Demonstrated experience delivering enterprise data, analytics, or AI solutions in large, complex manufacturing and supply-chain environments, across one or more functions such as planning, procurement, manufacturing, inventory, logistics, engineering, aftermarket, commercial, finance, or related operational areas.
Hands-on expertise with SQL and Python/PySpark, plus data modeling, scalable pipeline design, data integration, and distributed/cloud data platforms.
Experience designing, building, and operating batch and streaming or near-real-time data pipelines with orchestration, reliability, monitoring, recovery, scalability, and performance in mind.
Experience integrating data across complex enterprise source systems including ERP/operational systems, legacy databases, APIs, cloud platforms, event streams, IoT/telemetry sources, and structured or unstructured data.
Strong data modeling experience, including relational and dimensional modeling, fact and dimension structures, star or snowflake schemas, conformed dimensions, and modeling patterns supporting analytics, operational, and AI use cases.
Experience building reusable data engineering frameworks, shared data foundations, enterprise data models, and governed data products for multiple use cases.
Experience with enterprise data platforms such as Databricks, Snowflake, and Azure data services or comparable cloud technologies.
Ability to lead solutions through the full lifecycle, from business discovery and requirements through exploration, architecture, implementation, deployment, monitoring, optimization, and ongoing support.
Ability to collaborate across Business, Data Science, AI Engineering, Analytics, Enterprise Architecture, and platform and application teams.
Demonstrated understanding of data engineering and architecture foundations enabling advanced analytics, machine learning, GenAI, and other AI-enabled solutions while maintaining standards for data quality, governance, security, scalability, reuse, performance, and cost.

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 compliance

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

Relocation package: Yes.

Estimated salary range note: The salary range provided is a good faith estimate; the final offer will be determined after considering relevant factors, including qualifications and experience.

REQID: 2438266

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