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Data Platform Product Manager Jobs in Indiana (NOW HIRING)

Coastal

Data Platform Engineer (Data 360)

Indianapolis, IN

$109K - $131K/yr

... and product strategies, with a heavy emphasis on maximizing the Salesforce Data 360 (D360 ... Solid understanding of enterprise architecture patterns, API management, and real-time data ...

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Allegion

Senior Data Platform Engineer

Carmel, IN · On-site

$67.25 - $89.75/hr

With more than 30 brands, 12,000+ employees globally and products sold in 130 countries, we ... management. * Strong understanding of data security and compliance requirements, implementing ...

Allegion

Senior Data Platform Engineer

Carmel, IN

$67.25 - $89.75/hr

With more than 30 brands, 12,000+ employees globally and products sold in 130 countries, we ... management. * Strong understanding of data security and compliance requirements, implementing ...

Relativity

Product Manager - Enrichment

Indianapolis, IN · On-site

... data, discover the truth, and act on it. Our e-discovery platform is used by more than 13,000 ... The Product Management team is looking for aProduct Manager to lead the roadmap and success of ...

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All JobsData Platform Product JobsData Platform Product Manager JobsData Platform Product Manager Jobs in Indiana

Data Platform Product Manager information

See Indiana salary details

$49K

$151.7K

$187.5K

How much do data platform product manager jobs pay per year?

As of Jul 19, 2026, the average yearly pay for data platform product manager in Indiana is $151,684.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,200.00 and $187,500.00 per year, depending on experience, location, and employer.

How does a Data Platform Product Manager typically collaborate with engineering and data teams to deliver platform features?

A Data Platform Product Manager regularly works alongside engineering and data teams by defining product requirements, prioritizing the feature backlog, and ensuring alignment with business goals. They facilitate communication among stakeholders, translate complex technical needs into actionable tasks, and help resolve roadblocks that may arise during development. This collaborative approach ensures the platform evolves to meet both user expectations and technical constraints, fostering a shared sense of ownership and delivering robust, scalable solutions.

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

To thrive as a Data Platform Product Manager, you need a strong understanding of data architecture, product management principles, and analytics, often supported by a degree in computer science, engineering, or a related field. Familiarity with data warehousing technologies, cloud platforms (such as AWS, Azure, or GCP), and tools like SQL, Tableau, or Snowflake is typically required, and certifications in Agile or Scrum can be beneficial. Outstanding communication, stakeholder management, and strategic thinking are crucial soft skills that help bridge technical and business teams. These skills ensure successful product delivery, alignment with business goals, and the creation of scalable, effective data solutions.

What is a Data Platform Product Manager?

A Data Platform Product Manager is responsible for overseeing the development, management, and strategy of an organization’s data platform. They work closely with engineering, data science, and business teams to ensure the platform meets stakeholder needs, supports data-driven decision-making, and aligns with the company's objectives. Their duties typically include defining product requirements, prioritizing features, facilitating communication across teams, and monitoring platform performance and adoption.

What is the difference between Data Platform Product Manager vs Data Engineer?

AspectData Platform Product ManagerData Engineer
Primary FocusProduct strategy, roadmap, and stakeholder alignment for data platformsBuilding, maintaining, and optimizing data pipelines and infrastructure
Required SkillsProduct management, data domain knowledge, communication skillsProgramming, database management, ETL processes
Work EnvironmentCross-functional teams, product lifecycle managementData engineering teams, technical infrastructure
Common CertificationsCertified Scrum Product Owner, data management certificationsApache Spark, cloud platform certifications, SQL expertise

The Data Platform Product Manager focuses on defining the vision and strategy for data platforms, coordinating between stakeholders and engineering teams. In contrast, Data Engineers are responsible for implementing and maintaining the technical infrastructure. Both roles are essential in data-driven organizations but serve different functions within the data ecosystem.

What are popular job titles related to Data Platform Product Manager jobs in Indiana? For Data Platform Product Manager jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Data Platform Product Manager jobs in Indiana look for? The top searched job categories for Data Platform Product Manager jobs in Indiana are:
What cities in Indiana are hiring for Data Platform Product Manager jobs? Cities in Indiana with the most Data Platform Product Manager job openings:
Data Platform Product Manager jobs near you
Data Platform Engineer

Data Platform Engineer

Jms Technical Solutions

Indianapolis, IN • On-site

$80 - $85/hr

Contractor

Posted 24 days ago

Job description

25th June, 2026
Our client in Indianapolis, IN, is looking for a contract Data Platform Engineer to join their team!
This is a hybrid/full-time/12-month contract position
Hourly range based on experience: $80-$85/HR
Our client is looking for a Data Platform Engineer to help us support their continued growth. The Data Platform Engineer is responsible for building, implementing, and maintaining technical solutions that align with best-practice standards and client needs. Working closely with Data Architects, they provide technical execution and development support within Salesforce.com and other SaaS applications to support business and product strategies, with a heavy emphasis on maximizing the Salesforce Data 360 (D360) ecosystem.
A Data Platform Engineer participates in discovery sessions to understand client processes and challenges, translating documented solution designs into functional technical requirements and production-ready implementations. They provide collaborative execution and clear communication to the project and client team members to build a foundation for a trusted technical partnership.
Role Responsibilities:
  • Data Architecture & Infrastructure Implementation
    • Enterprise D360 Harmonization: Implement and maintain data structures that align with business needs, leveraging Salesforce Data 360 (D360) capabilities for unified profile management, data democratization, and real-time activation.
    • Modern Cloud Integration: Build and deploy data solutions that bridge enterprise cloud data platforms (Data Lakes/Warehouses) with the Salesforce ecosystem to address specific business needs, such as Business Intelligence (BI), ETL/ELT, and AI/ML initiatives.
    • Legacy Migration: Execute the migration, ingestion, and mapping of customer data from legacy systems and siloed databases into the Salesforce D360 platform.
    • Governance & Trust: Configure and maintain data accessibility, data privacy, granular security controls, and compliance with relevant regulations (e.g., GDPR, CCPA) and industry standards within the customer data ecosystem.
  • Data Modeling & Pipeline Engineering:
    • Ingestion & Streaming Pipelines: Develop, deploy, and maintain real-time streaming and batch data pipelines for ingesting, transforming, and loading high-volume enterprise data into Salesforce D360 from various cloud sources and APIs.
    • D360 Identity Resolution: Build and support scalable data models and metadata architectures within Salesforce D360, implementing identity resolution rules, reconciliation rules, and unified data graphs as designed.
    • Performance Optimization: Monitor, troubleshoot, and optimize query performance, calculated insights, identity resolution runs, and data transformation processes within the Salesforce D360 and underlying lakehouse environments.
  • Technical Execution and Collaboration:
    • Cross-Functional Collaboration: Collaborate actively with key stakeholders-including business users, data engineers, data scientists, and CRM IT teams-to understand technical specifications and deliver unified data solutions.
    • Ecosystem Implementation: Help evaluate, test, and integrate appropriate tools, connectors, and zero-copy/Zero-Data-Movement technologies for seamless data integration, transformation, and activation within the Salesforce D360 ecosystem.
    • Technical Guidance: Provide development-level support, code reviews, and best-practice engineering guidance to data engineering and CRM development teams.

Experience/Skills Required:
  • Experience: 3+ years of experience in data engineering, technical consulting, or database development for cloud data platforms with multiple enterprise workstreams.
  • Salesforce D360 (Data Cloud) Capabilities: Strong working knowledge of the data cloud architecture, including data models (DMOS, DSOs), identity resolution, data spaces, calculated insights, and activation targets.
  • Modern Data Methods: Familiarity and alignment with modern data architecture methods, including lakehouse architecture, zero-copy data sharing, and real-time data activation.
  • Broad Data Ecosystem Experience: Hands-on experience with enterprise database technology, cloud data warehouses (e.g., Snowflake, Databricks), ETL/ELT tools, data engineering pipelines, and data science principles.
  • Strong Communication: Excellent verbal and presentation abilities, capable of effectively communicating technical engineering concepts and data updates to stakeholders and team members.
  • Technical Tooling & Development: Strong proficiency with data-centric programming languages (such as SQL and Python) as well as Salesforce application development components (Apex, Flow, LWCs, MuleSoft).
  • Engineering Patterns: Solid understanding of enterprise architecture patterns, API management, and real-time data streaming technologies (e.g., Kafka, Amazon Kinesis).
  • Structured Data Modeling: Practical experience with data modeling methodologies (such as Kimball dimensional modeling, Star/Snowflake schemas, or Medallion Bronze/Silver/Gold structures) and mapping them into a canonical Customer 360 model.
  • US Authorization: Must have full-time permanent US work authorization.

Additional Preferred Experience/Skills:
  • Bachelor's Degree preferred, or equivalent experience.
  • Salesforce Certified Data Cloud Consultant or Accredited Professional designations.
  • Hands-on experience with core Salesforce CRM technology like Sales Cloud, Service Cloud, or Industry Clouds (e.g., Financial Services Cloud, Health Cloud).
  • Hands-on experience deploying AI/ML solutions like Salesforce Einstein, AWS Sagemaker, or Google Vertex AI, alongside a solid understanding of Generative AI patterns (e.g., Retrieval-Augmented Generation / RAG).
  • Experience designing data architectures on cloud platforms like Amazon Web Services, Microsoft Azure, or Google Cloud Platform.
  • Hands-on expertise with analytics and visualization tools like Tableau, CRM Analytics, Power BI, or Looker.
  • Open to travel based on client and business demands.

We are an equal-opportunity employer. We do not discriminate in hiring or employment against any individual based on race, color, gender, national origin, ancestry, religion, physical or mental disability, age, veteran status, sexual orientation, gender identity or expression, marital status, pregnancy, citizenship, or any other factor protected by anti-discrimination laws.

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