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Analytics Implementation Engineer Jobs in Indiana

Senior GenAI Engineer

Indianapolis, IN · On-site

$99K - $137K/yr

Maintain accountability for the integrity of code design, implementation, quality, data, and ... Lead requirement analysis, component design, development, unit testing, integrations, and support.

Senior Data Platform Engineer

Carmel, IN · On-site

$67.25 - $89.75/hr

Senior Data Platform Engineer This position serves as the senior technical expert for Data Hub processes within the Global Data & Analytics Team, owning the design and implementation of data ...

Senior Data Platform Engineer

Carmel, IN

$67.25 - $89.75/hr

Senior Data Platform Engineer This position serves as the senior technical expert for Data Hub processes within the Global Data & Analytics Team, owning the design and implementation of data ...

Engineer II

Indianapolis, IN · On-site

$93K - $127K/yr

Develop and implement engineering solutions, adhering to best practices and leveraging appropriate ... Strong problem-solving and analytical thinking skills. * Excellent communication and interpersonal ...

Engineer II

Indianapolis, IN

$93K - $127K/yr

Develop and implement engineering solutions, adhering to best practices and leveraging appropriate ... Strong problem-solving and analytical thinking skills. * Excellent communication and interpersonal ...

Engineer II

Indianapolis, IN · On-site

$93K - $127K/yr

Develop and implement engineering solutions, adhering to best practices and leveraging appropriate ... Strong problem-solving and analytical thinking skills. * Excellent communication and interpersonal ...

Lead and support root cause analysis and corrective actions for process-related non-conformances ... Design and implement tooling, fixtures, and automation systems to support manufacturing. Conduct ...

Quality Engineer

Jeffersonville, IN · On-site

$69K - $89K/yr

The Quality Engineer is responsible for ensuring that products and processes meet established ... Conduct root cause analysis of quality issues and implement corrective and preventive actions.

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Showing results 1-20

Analytics Implementation Engineer information

See Indiana salary details

$25

$48

$76

How much do analytics implementation engineer jobs pay per hour?

As of Jun 21, 2026, the average hourly pay for analytics implementation engineer in Indiana is $48.92, according to ZipRecruiter salary data. Most workers in this role earn between $36.59 and $58.08 per hour, depending on experience, location, and employer.

What is an Analytics Implementation Engineer?

An Analytics Implementation Engineer is a professional responsible for setting up, configuring, and maintaining digital analytics tools on websites and mobile applications. They work closely with stakeholders to understand business requirements, translate them into technical tracking specifications, and ensure accurate data collection for analysis. Their role often involves deploying tags, managing tag management systems, and troubleshooting data issues. This position requires a combination of technical skills, understanding of marketing analytics, and strong problem-solving abilities.

What are the key skills and qualifications needed to thrive as an Analytics Implementation Engineer, and why are they important?

To thrive as an Analytics Implementation Engineer, you need strong expertise in web analytics, JavaScript, tag management systems, and a background in computer science or a related field. Familiarity with tools like Google Tag Manager, Adobe Analytics, and certifications in analytics platforms are often expected. Attention to detail, problem-solving, and effective communication with stakeholders set top performers apart. These skills are vital for accurately collecting, interpreting, and communicating data to drive business insights and optimize digital experiences.

What is the difference between Analytics Implementation Engineer vs Data Analyst?

AspectAnalytics Implementation EngineerData Analyst
Required CredentialsBachelor's in CS, IT, or related field; certifications in analytics toolsBachelor's in Statistics, Math, or related field; often similar certifications
Work EnvironmentTechnical teams, project-based, focus on system setupBusiness units, reporting, data interpretation
Employer & Industry UsageTech companies, marketing agencies, e-commerceFinance, healthcare, retail, consulting

While both roles involve working with data, the Analytics Implementation Engineer primarily focuses on deploying and integrating analytics tools and systems, whereas the Data Analyst concentrates on analyzing data to generate insights. The roles often overlap in skills and certifications but differ in their core responsibilities and work environments.

What are some common challenges faced by Analytics Implementation Engineers when integrating analytics tools across multiple platforms?

Analytics Implementation Engineers often encounter challenges such as ensuring data consistency and accuracy across various digital platforms, dealing with legacy systems that may not easily support modern analytics tools, and navigating frequent updates or changes in website or app architectures. Close collaboration with development, product, and marketing teams is critical to clarify tracking requirements and maintain reliable data flows. Addressing these challenges requires a strong understanding of both the technical aspects of analytics tools and the business needs driving data collection.
What job categories do people searching Analytics Implementation Engineer jobs in Indiana look for? The top searched job categories for Analytics Implementation Engineer jobs in Indiana are:
What cities in Indiana are hiring for Analytics Implementation Engineer jobs? Cities in Indiana with the most Analytics Implementation Engineer job openings:
Senior GenAI Engineer

Senior GenAI Engineer

Deloitte

Indianapolis, IN • On-site

$99K - $137K/yr

Other

Posted 29 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

58th of 138 rated financial services


Job description

As a Senior GenAI Engineer, you will actively engage in your engineering craft, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users, while also driving tangible value for Deloitte's business investments. You will leverage your extensive GenAI & engineering craftmanship across multiple programming languages and modern frameworks, consistently demonstrating your strong track record in delivering high-quality, outcome-focused solutions. The ideal candidate will be a dependable team player, collaborating with cross-functional teams to design, develop, and deploy advanced software solutions..

Recruiting for this role ends on 29 June 2026.

Work You'll Do: 

  • Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, lean designs and implementations.Engineering Craftsmanship: Maintain accountability for the integrity of code design, implementation, quality, data, and ongoing maintenance and operations. Stay hands-on, self-driven, and continuously learn new approaches, languages, and frameworks with significant focus on infusing AI/ML/GenAI where possible/appropriate. Create technical specifications, and write high-quality, supportable, scalable code ensuring all quality KPIs are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams.Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning. Utilize a learning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions.Advanced Technical Proficiency: Possess deep expertise in modern software engineering practices and principles, including AI/ML/GenAI, Agile methodologies and DevSecOps to deliver daily product deployments using full automation from code check-in to production with all quality checks through SDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate understanding of the full lifecycle product development, focusing on continuous improvement and learning.Effective Communication and Influence: Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives.
  • Engagement and Collaborative Co-Creation: Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions.
  • Domain Expertise: Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff.
  • Cross-Functional Collaboration and Integration: Work collaboratively with empowered, cross-functional teams including product management, experience, and delivery. Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation.
  • Customer-Centric Engineering: Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time.
  • Technical Leadership and Advocacy: Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals. Lead requirement analysis, component design, development, unit testing, integrations, and support.

The Team

US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte's primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte's success. It is the engine that drives Deloitte, serving many of the world's largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence.

The successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

Qualifications

Required:

  • A bachelor's degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor.
  • Strong software engineering foundation with deep understanding of OOPs, data-structure, algorithms, code instrumentations, beautiful coding practices etc.
  • 5+ years of experience with AI/ML, with last 2 years focused on GenAI as well as technologies like OpenAI, Claude, Gemini, LangChain, Agents, Vector databases, and approaches like Prompt Engineering, fine-tuning, etc.
  • Proven experience in: Python, R, TensorFlow, PyTorch, Keras, Julia, ML libraries, NLP, etc.
  • Proven experience with big data technologies, Angular, React, NodeJS, Python, C#, .NET Core, Java, Golang, SQL/NoSQL.
  • Proven experience with cloud-native engineering, using FaaS/PaaS/micro-services on cloud hyper-scalers like Azure, AWS, and GCP.
  • Strong understanding of methodologies & tools like, XP, Lean, SAFe, DevSecOps, SRE, ADO, GitHub, SonarQube, etc.
  • Ability to travel 10%, on average, based on the work you do and products you build.
  • Limited immigration sponsorship may be available.

Preferred:

  • Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care.

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 $102,500 to $210,600.

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.

#EA_ExpHire
#EA_ITS_ExpHire
#PXE_JOBS

Qualifications:

As a Senior GenAI Engineer, you will actively engage in your engineering craft, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users, while also driving tangible value for Deloitte's business investments. You will leverage your extensive GenAI & engineering craftmanship across multiple programming languages and modern frameworks, consistently demonstrating your strong track record in delivering high-quality, outcome-focused solutions. The ideal candidate will be a dependable team player, collaborating with cross-functional teams to design, develop, and deploy advanced software solutions..

Recruiting for this role ends on 29 June 2026.

Work You'll Do: 

  • Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, lean designs and implementations.Engineering Craftsmanship: Maintain accountability for the integrity of code design, implementation, quality, data, and ongoing maintenance and operations. Stay hands-on, self-driven, and continuously learn new approaches, languages, and frameworks with significant focus on infusing AI/ML/GenAI where possible/appropriate. Create technical specifications, and write high-quality, supportable, scalable code ensuring all quality KPIs are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams.Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning. Utilize a learning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions.Advanced Technical Proficiency: Possess deep expertise in modern software engineering practices and principles, including AI/ML/GenAI, Agile methodologies and DevSecOps to deliver daily product deployments using full automation from code check-in to production with all quality checks through SDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate understanding of the full lifecycle product development, focusing on continuous improvement and learning.Effective Communication and Influence: Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives.
  • Engagement and Collaborative Co-Creation: Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions.
  • Domain Expertise: Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff.
  • Cross-Functional Collaboration and Integration: Work collaboratively with empowered, cross-functional teams including product management, experience, and delivery. Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation.
  • Customer-Centric Engineering: Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time.
  • Technical Leadership and Advocacy: Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals. Lead requirement analysis, component design, development, unit testing, integrations, and support.

The Team

US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte's primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte's success. It is the engine that drives Deloitte, serving many of the world's largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence.

The successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

Qualifications

Required:

  • A bachelor's degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor.
  • Strong software engineering foundation with deep understanding of OOPs, data-structure, algorithms, code instrumentations, beautiful coding practices etc.
  • 5+ years of experience with AI/ML, with last 2 years focused on GenAI as well as technologies like OpenAI, Claude, Gemini, LangChain, Agents, Vector databases, and approaches like Prompt Engineering, fine-tuning, etc.
  • Proven experience in: Python, R, TensorFlow, PyTorch, Keras, Julia, ML libraries, NLP, etc.
  • Proven experience with big data technologies, Angular, React, NodeJS, ...

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