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Salary
$20k – $50k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Middle · 3+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Autodesk is an American software company founded in 1982 that makes the design and engineering tools used to create buildings, infrastructure, products, factories and visual effects. AutoCAD established it as the standard for computer-aided drafting, and the portfolio now spans Revit for building information modelling, Fusion for product design and manufacturing, Civil 3D for infrastructure, and Maya and 3ds Max for film, television and games. Headquartered in San Francisco, the company moved fully to subscription licensing in the last decade and is pushing customers toward cloud platforms that connect design, construction and production data across a project's lifecycle.

Job Requisition ID #

26WD100390

Position Overview

We're hiring a Data Analytics Engineer to join Customer Success Analytics (CS Analytics) within Autodesk Customer Success. This role sits at the intersection of analytics engineering, business intelligence, and insight delivery. You will build Structured Query Language (SQL) models, data pipelines, and dashboards that power retention, expansion, and growth decisions across the business.

You will partner with Data Engineering, Data Science, and business stakeholders to define reliable metrics, maintain production analytics assets, and translate complex data into clear, actionable insights for Customer Success, Support, Finance, and executive audiences

Responsibilities

  • Develop production-grade Snowflake Structured Query Language (SQL) models, curated datasets, reusable metric logic, and dashboard-ready views using clean, modular engineering practices

  • Partner with stakeholders to define metrics, improve analytics capabilities, and support pipeline delivery using dbt, refresh workflows, and orchestration

  • Design and maintain interactive Microsoft Power BI and Tableau dashboards that communicate meaningful business insights and support executive decision-making

  • Apply business intelligence best practices, including intuitive dashboard design, metric consistency, performance optimization, and stakeholder validation

  • Conduct rigorous quantitative analysis across customer cohorts, retention, expansion, engagement, renewals, and business impact

  • Serve as a subject matter expert for data structures, data quality, and metric definitions while translating analytical findings into actionable recommendations

  • Use Python to support ad hoc analysis, data exploration, validation, automation, and quality control activities

  • Leverage Artificial Intelligence (AI)-assisted analytics tools such as Cursor, Claude, Snowflake Cortex, and internal conversational agents to accelerate exploration, SQL development, documentation, and insight generation while validating outputs for accuracy, reproducibility, and governance

  • Work within a Git-based version-controlled environment, following engineering best practices, peer reviews, and collaborative development standards

  • Communicate insights effectively through dashboards, written reports, presentations, and stakeholder discussions

Minimum Qualifications

  • 3+ years of relevant experience in a Software as a Service (SaaS) environment

  • Strong understanding of SaaS business models and key performance indicators, including retention, expansion, Annual Recurring Revenue (ARR), renewals, engagement, Net Promoter Score (NPS), Customer Satisfaction (CSAT), and utilization

  • Strong Structured Query Language (SQL) skills with hands-on experience using Snowflake or a comparable cloud data warehouse

  • Proven experience developing and maintaining production-grade analytics assets rather than ad hoc reporting solutions

  • Strong experience with Microsoft Power BI and/or Tableau, including designing intuitive dashboards, developing reusable business metrics, and creating executive-ready data stories

  • Experience applying statistical methods and hypothesis-driven analytical approaches

  • Strong communication and storytelling skills with the ability to influence business decisions using data

  • Experience working across Customer Success, Support, Finance, Renewals, and Product usage data domains

Preferred Qualifications

  • Experience using Python for analysis, notebooks, automation, or pipeline support

  • Familiarity with dbt, including models, testing, documentation, and analytics engineering workflows

  • Experience supporting Finance, Customer Success, Customer Support, Customer Service, or Renewals organizations

  • Experience using Artificial Intelligence (AI) and Large Language Model (LLM) tools for analytics, including Cursor, Claude, Snowflake Cortex, Copilot agents, or AI-assisted SQL, while following responsible AI practices

  • Experience with workflow orchestration tools such as Apache Airflow or similar scheduling frameworks

  • Familiarity with Git and collaborative software development practices

The Ideal Candidate

The ideal candidate is an analytical engineer who combines strong technical expertise, business acumen, and a passion for transforming data into actionable insights that influence strategic decision-making

  • Demonstrates strong analytical thinking and applies structured problem-solving approaches to complex business challenges

  • Builds scalable, maintainable, and reusable analytics assets that improve consistency, efficiency, and business decision-making

  • Uses sound judgment to validate data, metrics, and AI-assisted outputs while maintaining high standards of accuracy and governance

  • Balances technical excellence with business impact by translating complex analyses into clear and actionable recommendations

  • Collaborates effectively with Data Engineering, Data Science, Customer Success, Finance, and Product teams to solve cross-functional challenges

  • Takes ownership of analytics solutions from development through deployment, validation, and continuous improvement

  • Continuously improves engineering practices through automation, documentation, peer reviews, and knowledge sharing

  • Communicates confidently with technical and business stakeholders, including senior leadership

  • Demonstrates curiosity, adaptability, and a commitment to learning emerging analytics technologies and modern data engineering practices

  • Contributes to a collaborative, high-performing team culture while mentoring others and driving continuous improvement

#LI-GC3

Learn More

About Autodesk

Welcome to Autodesk! Amazing things are created every day with our software - from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.

We take great pride in our culture here at Autodesk - it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.

When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!

Salary transparency

Salary is one part of Autodesk’s competitive compensation package. Offers are based on the candidate’s experience and geographic location. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

Belonging

We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging

In-Person Onboarding and Identity Verification

This role may require in-person onboarding and/or in-person ID verification.

Are you an existing contractor or consultant with Autodesk?

Please search for open jobs and apply internally (not on this external site).

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