Autodesk
Technology
SeniorDataEngineer(Python,AI)
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Engineer (Python, AI) at Autodesk. Skills: Data Engineering, Data Pipelines, Cloud Data, AI/ML. Act as Data Champion. Drive data quality standards”
Industry & Context.
Break down complex problems; Define technical solutions; Solve hard problems; Data analysis; Data mining
What They're Looking For.
Must Have
6-8 years of experience, Proficiency in SQL, Proficiency in Python, Experience building data pipelines, Experience with modern data technologies, Experience with cloud-based data architectures, Experience building dashboards, Experience building analytics, Experience with version control, Experience with CI/CD tools, Experience with streaming architectures, Experience with Flink-based processing, Understanding of data modeling, Understanding of pipeline reliability, Understanding of large-scale data processing, Experience working with notebook solutions, Experience leveraging AI-assisted development tools, Familiarity with applying AI/ML techniques, Bachelor's degree in Computer science, Bachelor's degree in Engineering, Equivalent practical experience
Nice to Have
Experience with data platform modernization, Experience with large-scale data migrations, Experience with identity datasets, Experience with access datasets, Experience with compliance datasets, Experience with entitlement-related datasets, Familiarity with MCP servers, Familiarity with AI-agent frameworks
What You'll Do.
Drive data quality standards
Drive data reliability standards
Drive data observability standards
Improve data processing pipelines
Improve analytics pipelines
Solve problems around reliability
Solve problems around resiliency
Solve problems around scalability
Understand business requirements
Architect systems that scale
Architect systems that extend
Break down complex problems
Define technical solutions
Sequence work for improvements
Design data pipelines
Maintain data pipelines
Modernize legacy data workflows
Modernize legacy data infrastructure
Migrate from Hive to Iceberg
Develop ETL workflows
Develop ELT workflows
Serve data for analytics
Serve data for operational use cases
Interface with data engineers
Interface with data scientists
Interface with product managers
Understand stakeholder needs
Promote best practices
Identify business challenges
Identify opportunities for improvement
Solve challenges using data analysis
Solve challenges using data mining
Make strategic recommendations
Make tactical recommendations
Provide insights around product usage
Provide insights around campaign performance
Provide insights around funnel metrics
Provide insights around segmentation
Provide insights around conversion
Provide insights around revenue growth
Partner with different teams
Understand business needs
Understand business requirements
Own critical data pipelines
Contribute to improving data platform
How You'll Work.
Team & Collaboration
Interface with stakeholders; Partner with different teams
Full Job Description
**Job Requisition ID #** 26WD95826 **Position Overview ** Autodesk is looking for diverse engineering candidates to join the Access domain, building data Engineering pipelines leveraging data platforms. As a Data Engineer, you will act as a Data Champion, driving data quality, reliability, and observability standards across platforms. You will rapidly improve critical data processing and analytics pipelines while solving hard problems around reliability, resiliency, and scalability. Our tech stack includes Hive, Spark, Flink, Presto, Iceberg, Looker, Power BI, and cloud services on Amazon Web Services, with data platform components. Analytics and reporting leverage platforms from Snowflake, Google (Looker), and Microsoft (Power BI). **Roles and Responsibilities** * You will need a product-focused mindset. It is essential for you to understand business requirements and architect systems that scale and extend to accommodate those needs * Break down complex problems, define technical solutions, and sequence of work to enable fast, iterative improvements * Design, build, and maintain scalable data pipelines and data models across Access * Modernize legacy data workflows and infrastructure, including migrations from platforms such as Hive to Iceberg * Develop reliable ETL/ELT workflows to ingest, transform, and serve data for analytics and operational use cases * Interface with data engineers, data scientists, product managers, and other stakeholders to understand their needs and promote best practices * You have a growth mindset. You will identify business challenges and opportunities for improvement and solve them using data analysis and data mining to make strategic and tactical recommendations * Enable analytics and provide critical insights around product usage, campaign performance, funnel metrics, segmentation, conversion, and revenue growth * You will partner with different teams within the organization to understand business needs and requirements * Own critical
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