1

Data Engineer Gcp Data Engineer Jobs in Indiana (NOW HIRING)

Data Engineer - Senior

Indianapolis, IN · On-site

$109K - $131K/yr

We are looking for a talented Data Engineer- Senio r to join our team specializing in Systems/Information Technology for our Corporate organization in Indianapolis, IN . In this role, you will make ...

New

Data Engineer - Senior

Indianapolis, IN · On-site

$109K - $131K/yr

We are looking for a talented Data Engineer- Senio r to join our team specializing in Systems/Information Technology for our Corporate organization in Indianapolis, IN . In this role, you will make ...

New

Cloud Data Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

As a Cloud Data Engineer , you will build the modern Azure data platform that powers analytics, AI/ML, and enterprise integration for the missions our clients care about most. Your work makes it ...

New

Cloud Data Engineer

Indianapolis, IN

$109K - $131K/yr

As a Cloud Data Engineer , you will build the modern Azure data platform that powers analytics, AI/ML, and enterprise integration for the missions our clients care about most. Your work makes it ...

Cloud Data Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

As a Cloud Data Engineer , you will build the modern Azure data platform that powers analytics, AI/ML, and enterprise integration for the missions our clients care about most. Your work makes it ...

New

Cloud Data Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

As a Cloud Data Engineer , you will build the modern Azure data platform that powers analytics, AI/ML, and enterprise integration for the missions our clients care about most. Your work makes it ...

Data Engineer

Indianapolis, IN · Hybrid

$109K - $131K/yr

... and engineers to improve efficiency and data organization; improve performance through data structure and query optimization Ensure data integrity, quality, and security across all systems and ...

Data Engineer

Fort Wayne, IN · Hybrid

$113K - $135K/yr

... and engineers to improve efficiency and data organization; improve performance through data structure and query optimization Ensure data integrity, quality, and security across all systems and ...

As a Lead Platform Data Engineer, you will oversee the data architecture connecting product ... GCP). • Experience implementing Data Contracts, schema registries, and observability tools. • ...

Fabric Data Engineer

Fort Wayne, IN · On-site

$104K - $125K/yr

The Fabric Data Engineer is an integral member of Lasting Change's data platform team, contributing hands-on to the development, optimization, and governance of Petra, the organization's enterprise ...

Fabric Data Engineer

Fort Wayne, IN · On-site

$104K - $125K/yr

Description The Fabric Data Engineer is an integral member of Lasting Change's data platform team, contributing hands-on to the development, optimization, and governance of Petra, the organization ...

Data Engineer II

Fort Wayne, IN · On-site

$113K - $135K/yr

Data Engineer II FLSA Status: Exempt Job Family: IT - Business Intelligence Department: IT - Business Intelligence Location: Corporate Office (Fort Wayne, IN) JOB SUMMARY Responsible for designing ...

Data Engineer II

Fort Wayne, IN · On-site

$113K - $135K/yr

Data Engineer II FLSA Status: Exempt Job Family: IT - Business Intelligence Department: IT - Business Intelligence Location: Corporate Office (Fort Wayne, IN) JOB SUMMARY Responsible for designing ...

Data Engineer

New Albany, IN · On-site +1

$105K - $127K/yr

We are an engineering and innovation company working in different areas. Within the IT sector we have reinvented the future of data, integrating the most advanced techniques in artificial ...

Senior Data Engineer

Zionsville, IN · On-site

$102K - $139K/yr

Why This Role Matters: The Senior Data Engineer at Group 1001 will play a critical role in ... Experience with cloud platforms (AWS, Azure, GCP) and modern data architectures * Proven ability to ...

New

next page

Showing results 1-20

Data Engineer Gcp Data Engineer information

What is the difference between Data Engineer Gcp Data Engineer vs Data Engineer?

AspectData Engineer Gcp Data EngineerData Engineer
CertificationsGCP certifications (e.g., Professional Data Engineer)Varies; often includes cloud or database certifications
Work EnvironmentPrimarily cloud-based, focusing on Google Cloud Platform toolsCan be cloud, on-premises, or hybrid environments
Industry UsageCommon in organizations leveraging Google Cloud servicesWidespread across industries using various cloud providers
Skills FocusGCP tools, BigQuery, Dataflow, Pub/SubSQL, ETL, data modeling, general cloud skills

In summary, Data Engineer Gcp Data Engineer specializes in Google Cloud Platform tools and certifications, focusing on cloud-native data solutions. Data Engineer is a broader role that may work across multiple platforms and environments, with a wider range of tools and technologies.

What are some common challenges faced by Data Engineers working with GCP, and how can they be addressed?

Data Engineers working with Google Cloud Platform (GCP) often encounter challenges such as optimizing data pipeline performance, managing costs, and ensuring data security and compliance. Effective use of GCP's native monitoring and logging tools can help identify bottlenecks in ETL processes, while leveraging features like autoscaling in Dataflow or BigQuery partitioning improves efficiency. Regular collaboration with DevOps and security teams is crucial to maintain robust cloud architecture and compliance with data regulations. Staying updated with GCP releases and best practices will also help proactively address evolving challenges.

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

To thrive as a GCP Data Engineer, you need strong expertise in data modeling, ETL processes, and cloud architecture, typically backed by a degree in computer science or related field. Proficiency with Google Cloud Platform services (like BigQuery, Dataflow, and Pub/Sub), SQL, and tools such as Python or Java is essential, and certifications like Google Professional Data Engineer are highly valued. Strong problem-solving, communication, and teamwork skills help you collaborate effectively and translate business needs into technical solutions. These abilities ensure efficient, scalable data pipelines and reliable infrastructure, which are critical for driving data-driven decision-making.

What is a GCP Data Engineer?

A GCP Data Engineer is a data engineering professional who specializes in designing, building, and managing data processing systems on Google Cloud Platform (GCP). They work with cloud-based tools and services to collect, transform, and analyze large volumes of data, enabling organizations to gain insights and make data-driven decisions. GCP Data Engineers are proficient in technologies such as BigQuery, Dataflow, Pub/Sub, and Cloud Storage. Their role often involves ensuring data pipelines are reliable, scalable, and secure while optimizing performance and cost.
What are popular job titles related to Data Engineer Gcp Data Engineer jobs in Indiana? For Data Engineer Gcp Data Engineer jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Data Engineer Gcp Data Engineer jobs in Indiana look for? The top searched job categories for Data Engineer Gcp Data Engineer jobs in Indiana are:
What cities in Indiana are hiring for Data Engineer Gcp Data Engineer jobs? Cities in Indiana with the most Data Engineer Gcp Data Engineer job openings:
Data Engineer - Senior

Data Engineer - Senior

Cummins Inc.

Indianapolis, IN • On-site

$109K - $131K/yr

Full-time

Posted 2 days ago

New


Cummins rating

8.1

Company rating: 8.1 out of 10

Based on 253 frontline employees who took The Breakroom Quiz

108th of 529 rated manufacturers


Job description

We are looking for a talented Data Engineer- Senior to join our team specializing in Systems/Information Technology for our Corporate organization in Indianapolis, IN

In this role, you will make an impact in the following ways:

  • Enable reliable data flow at scale by designing and automating deployments for distributed systems that ingest and transform diverse data sources, ensuring consistent and seamless data availability across the organization.
  • Improve data trust and decision-making by building robust monitoring frameworks that quickly detect and resolve data quality and integrity issues before they impact analytics.
  • Strengthen data governance and compliance by implementing clear standards for metadata, access control, and data retention, making data easier to discover, secure, and use responsibly.
  • Accelerate analytics delivery by designing scalable, efficient data pipelines with built-in monitoring and alerting, reducing downtime and improving responsiveness to business needs.
  • Enhance system performance and efficiency by creating optimized physical data models, indexing strategies, and table relationships that reduce query times and resource usage.
  • Drive innovation through modern data architecture by leveraging cloud and distributed platforms (e.g., Data Lakes, NoSQL, Hadoop ecosystems) to support high-volume, high-velocity data processing.
  • Increase productivity through automation by eliminating repetitive manual tasks in data preparation and integration, reducing errors and freeing up teams for higher-value work.
  • Elevate team capability and delivery speed by mentoring teammates and applying Agile/DevOps practices, ensuring continuous improvement and successful execution of critical analytics initiatives
Cummins is an equal opportunity employer. Our policy is to provide equal employment opportunities to all qualified persons without regard to race, sex, color, disability, national origin, age, religion, union affiliation, sexual orientation, veteran status, citizenship, gender identity, or other status protected by law.

Core Responsibilities / Activities: 

  • Design and implement scalable and efficient data pipelines using Apache Spark and Databricks on Azure. 

  • Lead the complex transformation and integration of unstructured data sources into structured Delta Lake formats, applying software engineering best practices to ensure reliability, modularity, and reusability. 

  • Troubleshoot and optimize Spark jobs for performance, reliability, and cost-efficiency in a production environment. 

  • Drive continuous improvement of data engineering solutions by leveraging AI/ML and LLM-based techniques to enhance observability, performance optimization, and long-term maintainability. 

Skill, Education, or Experience Requirements: 

  • Minimum of 5 years of hands-on experience in data engineering with expertise in Azure Databricks and programming in Scala or Python. 

  • Proven experience in building and maintaining structured streaming pipelines using Spark. 

  • Strong knowledge of big data technologies, including Delta Lake, Apache Spark, Structured Streaming, and SQL. 

  • Experience with Git for version control and CI/CD pipeline management. 

Nice to Have (Preferences): 

  • Data Engineering Certification (e.g., Databricks Certified Data Engineer, Apache Spark Professional Data Engineer, or equivalent). 

  • Exposure to real-time data ingestion frameworks and cloud-native data services (e.g., Azure Event Hub, Azure Data Lake, AWS SQS, etc). 

  • Familiarity with data governance, access control (e.g., Unity Catalog or Immuta), and performance monitoring tools in cloud environments. 

To be successful in this role you will need the following:

  • System Requirements Engineering  - Uses appropriate methods and tools to translate stakeholder needs into verifiable requirements to which designs are developed; establishes acceptance criteria for the system of interest through analysis, allocation and negotiation; tracks the status of requirements throughout the system lifecycle; assesses the impact of changes to system requirements on project scope, schedule, and resources; creates and maintains information linkages to related artifacts.
     
  • Collaborates - Building partnerships and working collaboratively with others to meet shared objectives.
     
  • Communicates effectively - Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences.
     
  • Customer focus - Building strong customer relationships and delivering customer-centric solutions.
     
  • Decision quality - Making good and timely decisions that keep the organization moving forward.
     
  • Data Extraction - Performs data extract-transform-load (ETL) activities from variety of sources and transforms them for consumption by various downstream applications and users using appropriate tools and technologies.
     
  • Programming - Creates, writes and tests computer code, test scripts, and build scripts using algorithmic analysis and design, industry standards and tools, version control, and build and test automation to meet business, technical, security, governance and compliance requirements.
     
  • Quality Assurance Metrics - Applies the science of measurement to assess whether a solution meets its intended outcomes using the IT Operating Model (ITOM), including the SDLC standards, tools, metrics and key performance indicators, to deliver a quality product.
     
  • Solution Documentation - Documents information and solution based on knowledge gained as part of product development activities; communicates to stakeholders with the goal of enabling improved productivity and effective knowledge transfer to others who were not originally part of the initial learning.
     
  • Solution Validation Testing - Validates a configuration item change or solution using the Function's defined best practices, including the Systems Development Life Cycle (SDLC) standards, tools and metrics, to ensure that it works as designed and meets customer requirements.
     
  • Data Quality - Identifies, understands and corrects flaws in data that supports effective information governance across operational business processes and decision making.
     
  • Problem Solving - Solves problems and may mentor others on effective problem solving by using a systematic analysis process by leveraging industry standard methodologies to create problem traceability and protect the customer; determines the assignable cause; implements robust, data-based solutions; identifies the systemic root causes and ensures actions to prevent problem reoccurrence are implemented.
     
  • Values differences - Recognizing the value that different perspectives and cultures bring to an organization. 

Education, Licenses, Certifications: 
 

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

Experience: 
 

Intermediate experience in a relevant discipline area is required. Knowledge of the latest technologies and trends in data engineering are highly preferred and includes:


- Familiarity analyzing complex business systems, industry requirements, and/or data regulations
- Background in processing and managing large data sets
- Design and development for a Big Data platform using open source and third-party tools
- SPARK, Scala/Java, Map-Reduce, Hive, Hbase, and Kafka or equivalent college coursework
- SQL query language
- Clustered compute cloud-based implementation experience
- Experience developing applications requiring large file movement for a Cloud-based environment and other data extraction tools and methods from a variety of sources
- Experience in building analytical solutions 
Intermediate experiences in the following are preferred:
- Experience with IoT technology 
- Experience in Agile software development


What Cummins employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Cummins logo

About Cummins

Sourced by ZipRecruiter

Cummins Inc., headquartered in Columbus, IN, US, is a global power leader that designs, manufactures, and distributes numerous power products and systems. With its genesis from as early as 1919, the company readily serves diverse industries such as transportation, industrial, generator drive, or marine applications, among others. At the heart of Cummins' operations, its key product lineup encompasses diesel & natural gas engines, generator sets, engine components, and filtration, emission solutions, and electrical power generation systems. Cummins deeply embodies core values of integrity, respect for diversity, teamwork, performance excellence, and social responsibility - all of which dynamically fuel their mission 'Making people's lives better by powering a more prosperous world'.

Industry

Transportation equipment manufacturing

Company size

10,000+ Employees

Headquarters location

Columbus, IN, US

Year founded

1919