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Data Manager Jobs in Indiana (NOW HIRING)

USM

Data Scientist

Columbus, IN

... M counselling, Product Engineering, Business Intelligence, Data Management, SOA, BPM, Data ... Warehousing, SharePoint Consulting and IT Infrastructure. Our other offerings include modified ...

Parkview Health

Data Engineer I

Fort Wayne, IN

$113K - $135K/yr

Data Management: Assists in developing and maintaining simple ETL processes. Supports building data pipelines to collect and move data from source systems to storage platforms. Helps with data ...

Parkview Health

Data Engineer I

Fort Wayne, IN

$113K - $135K/yr

Data Management: Assists in developing and maintaining simple ETL processes. Supports building data pipelines to collect and move data from source systems to storage platforms. Helps with data ...

Parkview Health

Data Engineer I

Fort Wayne, IN · On-site

$113K - $135K/yr

Data Management: Assists in developing and maintaining simple ETL processes. Supports building data pipelines to collect and move data from source systems to storage platforms. Helps with data ...

Pwc

Data Engineer - Manager

Indianapolis, IN

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and ...

Pwc

Data Engineer - Manager

Indianapolis, IN · On-site

$99K - $232K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary The Opportunity As a Data Engineer - Manager, you will play a pivotal role in transforming raw data ...

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All JobsData JobsData Manager JobsData Manager Jobs in Indiana

Data Manager information

See Indiana salary details

$29.5K

$92.4K

$163.7K

How much do data manager jobs pay per year?

As of Jul 10, 2026, the average yearly pay for data manager 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 is the salary of a data manager?

The salary of a data manager typically ranges from $70,000 to $120,000 annually, depending on experience, industry, and location. Professionals with advanced skills in database management, data analysis, and familiarity with tools like SQL or Python tend to earn higher salaries.

What is a Data Manager?

A Data Manager is a professional responsible for overseeing the collection, storage, organization, and safeguarding of data within an organization. They ensure that data is accurate, accessible, and secure, often working with databases and data management systems. Data Managers also develop data policies, maintain data quality, and support teams in using data effectively for decision-making. Their role is crucial in industries where large volumes of information are handled, such as healthcare, finance, and research.

What is the difference between Data Manager vs Data Analyst?

AspectData ManagerData Analyst
Required CredentialsBachelor's degree in IT, Computer Science, or related field; certifications like CDMP or DAMA often preferredBachelor's degree in Statistics, Mathematics, or related field; certifications like CAP or Microsoft Data Analyst are common
Work EnvironmentTypically manages data systems, databases, and teams; works in IT or data departmentsAnalyzes data sets, creates reports, and visualizations; often works in business or analytics teams
Employer & Industry UsageUsed across industries like healthcare, finance, and tech for data governance and managementCommon in marketing, finance, and consulting for insights and decision-making

While both roles involve working with data, Data Managers focus on overseeing data systems and ensuring data quality, whereas Data Analysts interpret data to generate insights. Understanding these differences helps in choosing the right career path or job search focus.

What Is a Data Manager?

A data manager is responsible for creating and managing databases that meet the specific needs of a company or organization. As a data manager, your job duties include assessing customer database requirements, modifying the structure of existing databases, and handling the backup and recovery of older systems. You should have experience working with many database system varieties and large volumes of customer records. You can find data manager positions in a wide range of industries.

What jobs pay 200,000 a year in the USA?

Data managers typically do not earn $200,000 annually unless they hold senior or specialized roles such as Director of Data or Chief Data Officer, which require extensive experience, advanced skills in data analysis and management tools, and often leadership responsibilities. High-paying roles in data management are usually found in large corporations or industries like finance, technology, and healthcare. Salary levels depend on experience, education, certifications, and the size of the organization.

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

To thrive as a Data Manager, you need expertise in data management principles, database administration, and data governance, often supported by a bachelor's degree in computer science or a related field. Familiarity with SQL, data warehousing tools, data visualization platforms, and certifications like CDMP or DAMA are typically required. Strong analytical thinking, attention to detail, and effective communication are essential soft skills for ensuring data integrity and collaborating with stakeholders. These skills and qualifications are crucial for maintaining secure, accurate data systems and supporting informed business decisions.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst; many professionals transition into the field later in life. Success depends on acquiring relevant skills such as data analysis, SQL, and visualization tools, along with continuous learning and certification if needed.

How does a Data Manager typically collaborate with other departments to ensure data integrity?

As a Data Manager, collaboration with various departments—such as IT, analytics, and operations—is essential to maintain data integrity and consistency. You’ll regularly coordinate with these teams to establish data governance protocols, resolve discrepancies, and ensure that data collection and storage meet organizational standards. Open communication and regular meetings help address data quality issues and align data management practices across the organization. This cross-functional work not only supports accurate reporting but also drives better decision-making company-wide.

What is the role of a data manager?

A data manager is responsible for overseeing the collection, storage, organization, and maintenance of data within an organization. They ensure data quality, security, and accessibility, often using database management tools and following data governance standards. Their role supports data analysis and decision-making processes.
More about Data Manager jobs
What are the most commonly searched types of Data jobs in Indiana? The most popular types of Data jobs in Indiana are:
What are popular job titles related to Data Manager jobs in Indiana? For Data Manager jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Data Manager jobs in Indiana look for? The top searched job categories for Data Manager jobs in Indiana are:
What cities in Indiana are hiring for Data Manager jobs? Cities in Indiana with the most Data Manager job openings:
Data Manager jobs near you
Data Engineer/Senior Data Engineer, Data and Science

Data Engineer/Senior Data Engineer, Data and Science

Aircall

Francisco, IN • On-site, Remote

$130K - $200K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 16 days ago

Job description

Aircall is a unicorn, AI-powered customer communications platform used by 22,000+ companies worldwide to drive revenue, resolve issues faster, and scale customer-facing teams. We're redefining customer communications by bringing voice, SMS, WhatsApp, and AI together into one seamless workspace.
 
Our momentum comes from a simple idea: help teams work smarter, not harder. Aircall's AI Voice Agent automates routine calls, AI Assist streamlines post-call work, and AI Assist Pro delivers real-time guidance so people can do their best work. The result is higher revenue, faster resolutions, and teams that scale with confidence.
 
Aircall is headquartered in Paris, our European HQ, with a strong North American presence anchored in Seattle, our North American HQ, and teams across Madrid, London, Berlin, San Francisco, New York City, Sydney, and Mexico City. We've built a product customers love and a business that's scaling quickly, backed by world-class investors and driven by rapid AI innovation across multiple product lines.
At Aircall, you'll join a company in motion. We're ambitious, product-driven, and execution-focused, with visible impact, fast decisions, and real growth.
 
How we work at Aircall: We're customer-obsessed, data-driven, and focused on delivering meaningful outcomes. We value ownership, continuous learning, and thoughtful speed. If you thrive in a collaborative, fast-moving environment where trust and impact matter, you'll feel at home here.

About the role
The Data Engineering team at Aircall works on providing high-quality, reliable, and actionable data. As an AI-first data team, we are currently in a pivotal transition to build a robust semantic layer that will power our AI-first data platform, enabling analytics at speed and democratizing intelligent insights across the company. Some of the key problems we are currently solving include taking charge of data reliability, integrating new sources for raw data ingestion, and building sophisticated data models to power real-time dashboards and predictive analytics.
 
In this role, you will be instrumental in building new datasets for high-impact use cases such as churn prediction and feature adoption, while owning the end-to-end reliability and scalability of our data pipelines. You will work closely with Product and GTM business teams, sitting at the heart of a larger data organization alongside Data Science, Analytics, and Applied Scientists to bridge the gap between raw data and AI-driven decision-making.    
Responsibilities
  • Design, build and maintain core data infrastructure pieces that allow Aircall to support our many data use cases.
  • Enhance the data stack, lineage monitoring and alerting to prevent incidents and improve data quality.
  • Implement best practices for data management, storage and security to ensure data integrity and compliance with regulations.
  • Own the core company data pipeline, responsible for converting business needs to efficient & reliable data pipelines.
  • Participate in code reviews to ensure code quality and share knowledge.
  • Lead efforts to evaluate and integrate new technologies and tools to enhance our data infrastructure.
  • Define and manage evolving data models and data schemas. Manage SLA for data sets that power our company metrics. 
  • Collaborate with applied scientists, data scientists, analysts and other business stakeholders  to drive efficiencies for their work, supporting complex data processing, storage and orchestration
A little more about you:
  • Bachelor's degree or higher in Computer Science, Engineering, or a related field.
  • 3+ years of experience in data engineering, with a strong focus on designing and building data pipelines and infrastructure.
  • Proficient in SQL and Python, with the ability to translate complexity into efficient code.
  • Experience with data workflow development and management tools (dbt, Airflow).
  • Solid understanding of distributed computing principles and experience with cloud-based data platforms such as AWS, GCP, or Azure.
  • Strong analytical and problem-solving skills, with the ability to effectively troubleshoot complex data issues.Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.
  • Prior experience designing AI-ready data semantic layer is a major plus, specifically for enabling low-latency, high-fidelity analytics at scale.
  • Experience with data tooling, data governance, business intelligence and data privacy is a plus.
$130,000 - $200,000 a year
This is not including equity and other benefits. The actual salary offered will carefully consider a wide range of factors, including your skills, qualifications, and experience.
Why join us?
 
Key moment to join Aircall in terms of growth and opportunities
Our people matter, work-life balance is important at Aircall
Fast-learning environment, entrepreneurial and strong team spirit
45+ Nationalities: cosmopolite & multi-cultural mindset
Competitive salary package & benefits
Medical, dental, and vision insurance is 100% covered
 401k plan with company matching!
 Unlimited PTO - take the time you need to come to work feeling great!
 Wellness, commuter, and childcare reimbursements
 Generous parental leave policy
 
DE&I Statement: 
At Aircall, we believe diversity, equity and inclusion - irrespective of origins, identity, background and orientations - are core to our journey. 
 
We pride ourselves on promoting active inclusion within our business to foster a strong sense of belonging for all. We're working to create a place filled with diverse people who can enrich and learn from one another. We're committed to ensuring that everyone not only has a seat at the table but is valued and respected at it by providing equal opportunities to develop and thrive.  
 
We will constantly challenge ourselves to make sure that we live up to our ambitions around diversity, equity and inclusion, and keep this conversation open. Above all else, we understand and acknowledge that we have work to do and much to learn.
 
Want to know more about candidate privacy? Find our Candidate Privacy Notice here.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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