Data Engineer

Data Engineer

We are looking for a highly capable Data Engineer to join the Customer Success Management (CSM) Data & Analytics team at Autodesk. Data and analytics are increasingly central to how the business operates. Within the CSM organization, delivering trusted, timely, and scalable data assets that support onboarding, adoption, and customer engagement is a strategic priority. The Data & Analytics team is responsible for simplifying a complex data landscape and enabling self-serve, lifecycle-aware analytics that support Customer Success across a large and diverse customer base.

In this role, you will design, build, and maintain robust data pipelines, analytical datasets, and data frameworks that power reporting, dashboards, experimentation, and emerging AI-assisted insights. You will work closely with BI Developers, analysts, and cross-functional partners to ensure data is reliable, well-modelled, and fit for decision-making. This is a hands-on engineering role for someone who enjoys working at the intersection of data engineering, analytics, and business impact.

Roles and Responsibilities

• Design, build, and maintain scalable data pipelines for extracting, transforming, validating, and loading data from a wide variety of internal sources using Python, SQL, dbt, and workflow orchestration tools
• Develop and maintain trusted, reusable analytical datasets that serve as core building blocks for BI, self-service analytics, experimentation, and advanced insights
• Partner closely with BI Developers and analysts to translate business requirements into well-structured, performant data models
• Implement and maintain data quality, observability, and durability mechanisms to proactively detect and resolve issues across ingestion, transformation, and storage
• Optimize existing workflows, transformations, and queries to improve performance, reliability, and cost efficiency, particularly within Snowflake
• Design and evolve components of analytics engineering frameworks that support testing, documentation, governance, and consistency at scale
• Collaborate with Customer Success stakeholders to understand analytical needs and ensure data solutions align with business strategy and growth priorities
• Support downstream data consumers by answering questions, documenting datasets, and enabling effective self-service usage
• Stay current with data and analytics engineering best practices and evaluate new tools and technologies in the context of Autodesk's data strategy

AI & Advanced Analytics Enablement (Key Focus)

• This role does not own machine learning model development, but plays an important role in enabling AI-driven and predictive analytics through strong data foundations
• Prepare, transform, and serve high-quality analytical datasets used as inputs for predictive models and advanced analytics
• Operationalize model outputs (e.g., scores, classifications, predictions) into analytics layers and BI tools so insights are consumable by non-technical users
• Collaborate with data science and advanced analytics partners to productionize AI use cases, including feature engineering, validation, and monitoring
• Apply an understanding of responsible AI principles, including data quality, transparency, and explainability, particularly for customer-facing insights

Minimum Qualifications

• 4–6+ years of relevant professional experience in data engineering, analytics engineering, or a closely related role
• BA / BS in Data Science, Computer Science, Statistics, Mathematics, or equivalent practical experience
• Strong experience building and maintaining data pipelines, transformations, and analytical datasets
• Hands-on experience with Snowflake, including SnowSQL, Snowpipe, and cost/performance optimization
• Strong programming skills in Python and SQL, with an emphasis on modular, maintainable code
• Experience using dbt for analytics engineering and transformations
• Experience with workflow orchestration tools such as Airflow
• Experience working with version control systems (e.g., Git)

Preferred Qualifications

• Experience supporting Customer Success, Support, or GTM analytics use cases
• Familiarity with Power BI or other modern BI tools
• Experience working in cloud environments (e.g., AWS: S3, Lambda, Glue, CloudWatch)
• Basic understanding of Salesforce, Gainsight, or similar CS platforms
• Experience working with distributed or remote teams across time zones
• A strong curiosity for learning and improving data systems over time

The Ideal Candidate

• You enjoy working with complex, messy data and turning it into reliable analytical assets
• You care about business relevance and want to ensure data supports real decision-making
• You're comfortable with ambiguity and can translate loosely defined questions into concrete technical solutions
• You enjoy collaborating with BI Developers, analysts, and business stakeholders
• You have a strong sense of ownership and are comfortable operating in a self-guided manner