1

Senior Analytics Engineer Jobs in Indiana (NOW HIRING)

Sr. Data Engineer

Indianapolis, IN · On-site

$89 - $139/hr

The Senior Data Engineer will work closely with analytics, data science, and business stakeholders to standardize data definitions, improve data quality, and reduce reliance on manual data ...

New

The Senior Reliability Engineer I will perform failure probability and maintainability analysis within a team in support of the analysis and sustainment of developing equipment and systems, devices ...

The Senior Reliability Engineer I will perform failure probability and maintainability analysis within a team in support of the analysis and sustainment of developing equipment and systems, devices ...

Sr. Data Engineer

Indianapolis, IN · On-site

$109K - $131K/yr

The Senior Data Engineer will work closely with analytics, data science, and business stakeholders to standardize data definitions, improve data quality, and reduce reliance on manual data ...

Sr. Equipment Engineer

Jeffersonville, IN · On-site

$100K - $137K/yr

Senior Equipment Engineer II Department : US Equipment Entity: USCM Reports To: Senior Principal ... Analyze complex equipment performance data, identify trends, and implement innovative solutions for ...

Showing results 41-60

Senior Analytics Engineer information

See Indiana salary details

$56.6K

$120.4K

$174.6K

How much do senior analytics engineer jobs pay per year?

As of Sep 4, 2026, the average yearly pay for senior analytics engineer in Indiana is $120,427.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,400.00 and $136,500.00 per year, depending on experience, location, and employer.

What is a senior analytics engineer?

A Senior Analytics Engineer is a data professional who bridges the gap between data engineering and data analysis. They design, build, and maintain data pipelines, data models, and analytics infrastructure to ensure that data is reliable, accessible, and well-structured for analysis. Typically, they work with tools like SQL, dbt, and cloud data warehouses, collaborating closely with data analysts and business stakeholders to deliver actionable insights. Their role often involves optimizing data workflows, implementing best practices, and mentoring junior team members.

How does a senior analytics engineer typically collaborate with data scientists and business stakeholders?

Senior Analytics Engineers play a vital role in bridging the gap between raw data and actionable insights. They work closely with data scientists to ensure that data pipelines and models are robust, scalable, and well-documented. Additionally, they frequently meet with business stakeholders to understand reporting needs and translate them into technical requirements, ensuring that analytics solutions align with organizational goals. This collaborative approach helps maintain data quality and accelerates the delivery of meaningful analyses across teams.

What are the key skills and qualifications needed to thrive as a senior analytics engineer, and why are they important?

To thrive as a Senior Analytics Engineer, you need strong expertise in data modeling, SQL, data warehousing, and analytics, typically backed by a degree in computer science, mathematics, or a related field. Proficiency with tools such as dbt, Python, cloud data platforms (like Snowflake or BigQuery), and experience with BI tools are commonly required, along with certifications in analytics or cloud technologies being a plus. Excellent problem-solving, communication, and stakeholder management skills help you translate business requirements into robust data solutions. These skills ensure data integrity, drive actionable insights, and support effective decision-making across the organization.

What is the difference between Senior Analytics Engineer vs Data Engineer?

AspectSenior Analytics EngineerData Engineer
Required CredentialsBachelor's/Master's in CS, Analytics, or related; SQL, Python, data visualization skillsBachelor's/Master's in CS, Data Engineering, or related; SQL, Python, ETL tools skills
Work EnvironmentFocus on data analysis, reporting, and insights; collaborates with data teams and business unitsFocus on data pipeline development, infrastructure, and storage; works closely with data infrastructure teams
Employer & Industry UsageUsed across tech, finance, healthcare, and retail for analytics rolesCommon in tech, finance, and data-driven industries for building data systems

While both roles require strong SQL and Python skills, Senior Analytics Engineers primarily focus on analyzing data, creating reports, and deriving insights for business decisions. Data Engineers build and maintain the data infrastructure, pipelines, and storage systems. The roles often collaborate but serve different functions within data teams.

What are popular job titles related to Senior Analytics Engineer jobs in Indiana?

For Senior Analytics Engineer jobs in Indiana, the most frequently searched job titles are:

What cities in Indiana are hiring for Senior Analytics Engineer jobs?

Cities in Indiana with the most Senior Analytics Engineer job openings:

Infographic showing various Senior Analytics Engineer job openings in Indiana as of August 2026, with employment types broken down into 90% Full Time, 6% Part Time, and 4% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $120,427 per year, or $57.9 per hour.

Senior Forward Deployed Engineer- AWS

Deloitte

Indianapolis, IN

$99K - $137K/yr

Full-time

Re-posted 26 days ago


Key responsibilities

  • Work side by side with senior client team members to prototype and deliver high-impact GenAI-enabled solutions.

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms, ensuring production-quality code.

  • Engage with clients to identify business needs, translate high-value GenAI use cases into solutions, and lead working sessions to shape outcomes.


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz

47th of 154 rated financial services


Job description

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Work you'll do

As an AWS AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 5+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with AWS AI&Data including hands on experience with one of the following key platforms/products: Amazon Bedrock, Bedrock AgentCore, Strands Agents SDK, Knowledge Bases, Guardrails
  • 1+ years of experience with AWS Neptune and OpenSearch
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • At least 3 of 6 certifications from the following list: AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate)
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience with SageMaker fine-tuning (SFT and RFT) for domain SLMs
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


Qualifications:

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Work you'll do

As an AWS AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 5+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with AWS AI&Data including hands on experience with one of the following key platforms/products: Amazon Bedrock, Bedrock AgentCore, Strands Agents SDK, Knowledge Bases, Guardrails
  • 1+ years of experience with AWS Neptune and OpenSearch
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • At least 3 of 6 certifications from the following list: AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate)
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience with SageMaker fine-tuning (SFT and RFT) for domain SLMs
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


Education:Bachelor's DegreeEmployment Type:

What Deloitte employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom