Data Analytics Engineer

Autodesk is hiring a Data Analytics Engineer in Bengaluru.

Job Requisition ID # 26WD100393 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, where you'll build the Structured Query Language (SQL) models, data pipelines, and dashboards that power retention, expansion, and growth decisions across the business.

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 business metrics, improve analytics capabilities, and support pipeline delivery through dbt, refresh workflows, and orchestration

• Design and maintain interactive Microsoft Power BI and Tableau dashboards that deliver clear, actionable 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 on 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

Requirements

• 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 and interactive dashboards

• Developing trusted, reusable business metrics

• Translating analytical findings into 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 building scalable analytics solutions that enable data-driven decision-making across the organization

• Demonstrates strong analytical thinking and applies structured problem-solving approaches to solve 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 quality and governance

• Translates complex data into clear, actionable insights that influence strategic decisions and business outcomes

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

• 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 both technical and business stakeholders, including senior leadership

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 define