Description
Autodesk is looking for a talented Data Engineer to design, prototype, automate, and enable data-ingestion and integration solutions, and scalable data pipelines, for customer-facing engagements.
This role works in Technical Advisory, at the intersection of data engineering, Autodesk technology, and technical consulting delivery. The successful candidate will build reusable tools and accelerators that streamline customer data flows, especially around Autodesk Datum, ACC, Forma, APS APIs, model-derived data, ETL processing, and modern cloud technologies.
The role requires someone who can move from ambiguous customer requirements to practical working prototypes, feasibility demos, technical documentation, and reusable implementation patterns. The Data Engineer will collaborate with Technical Advisory consultants, product teams, data engineers, solution architects, project managers, and customer stakeholders to validate feasibility, reduce delivery effort, and create repeatable service offerings.
Main Responsibilities
- Design, build, and support reusable ETL tools, prototypes, and accelerators for Technical Advisory and customer-facing engagements
- Develop data-ingestion workflows, and data integrations for Autodesk Platforms and other modern engineering data sources
- Create and maintain reusable code, ETL processing tools, and configuration patterns for model-data extraction, and data-standardization workflows
- Support feasibility studies, demos, pilots, and proof-of-concept work for customer engagements, especially where requirements are unclear or the technical path needs validation
- Build proof-of-concept MCP servers, API wrappers, and integration layers that allow AI agents to query, validate, transform, or reason over customer data
- Design and prototype AI-enabled workflows that connect LLMs and agents with Autodesk platform data, customer data, and Technical Advisory delivery workflows
- Collaborate with product, platform, security, and consulting teams to align AI/MCP deliveries with Autodesk strategy, policy, and customer-delivery standards
- Translate customer and stakeholder needs into technical options, risks, assumptions, implementation plans, and demo-ready solutions
- Perform system-readiness and integration validation, including checks around connectivity, authorization, operating-system compatibility, sandbox readiness, and platform configuration
- Prepare technical documentation, configuration guidance, readiness summaries, data-source assessments, and reusable implementation notes for internal teams and customers
- Identify technical risks early, communicate blockers clearly, document findings, and recommend practical next steps
Minimum qualifications
- Strong command of Polish, both written and spoken
- 5+ years of data engineering, software engineering, or technical implementation experience involving data processing in cloud-based infrastructure, ETL, APIs, or cloud/platform integrations
- Hands-on Python development experience
- Strong SQL and data-modeling skills, and analytical data warehouses such as Snowflake
- Understanding of data-engineering best practices for medium-to-large-scale production workloads
- Experience designing and implementing ETL or ELT workflows, including data extraction, transformation, validation, mapping, and loading
- Experience working with APIs, authentication flows, and system integrations
- Ability to analyze ambiguous requirements, identify technical risks, and turn early-stage customer needs into working prototypes or feasibility demos
- Strong written and verbal communication skills, with the ability to explain technical findings to other stakeholders
- Service-oriented mindset and comfort working in consulting-style environments where timelines, scope, and technical clarity may change
- Ability to document technical solutions, assumptions, constraints, and configuration steps clearly enough for reuse by other teams
Preferred qualifications
- Experience building reusable tools or accelerators for consulting delivery
- Experience with desktop or lightweight web applications, including UI, authentication, and file-processing workflows
- Experience with orchestration, automation, or CI/CD tooling such as Git, Jenkins, Terraform, or similar
- REST API design and implementation experience
- Experience with cloud services and serverless technologies
- Experience with DBT, shell scripting, or similar tooling
- Experience with AI/MCP concepts, especially where agents or conversational interfaces interact with engineering data or Autodesk APIs