Job Requisition ID #26WD101237
Position OverviewWe are looking for an exceptional analytics/data engineer to transform, optimize, test, and maintain architectures for enterprise analytics databases, data pipelines, and processing systems, as well as optimizing data flow and collection for cross functional teams. The mission of the team is to empower decision makers and the broader data communities through trusted data assets and scalable self-serve analytics. The focus of your work will be engineering new pipelines and maintaining, creating frameworks, enhancing existing data pipeline with new features to ensure accurate data delivery to stakeholders in a timely manner, also support ad-hoc reporting requirements that facilitate data-driven actionable insights and decision making at Autodesk.
Responsibilities- Maintain/develop data pipelines required for the extraction, transformation, cleaning, pre-processing, aggregation and loading of data from a wide variety of data sources into Snowflake or Hive warehouses using Python, SQL, DBT, other data technologies
- Design, implement, test and maintain data pipelines/ new features based on stakeholders' requirements
- Develop/maintain scalable, available, quality assured analytical building blocks/datasets by close coordination with data analysts
- Optimize/ maintain workflows/ scripts on present data warehouses and present ETL
- Design / develop / maintain components of data processing frameworks
- Basic Knowledge of using LLMs and using AI tools like Co-pilot for development purposes
- Build and maintain data quality and durability tracking mechanisms in order to provide visibility into and address inevitable disruptions in data ingestion, processing, and storage
- Translate deeply technical designs into business appropriate representations as well as analyze business needs and requirements ensuring implementation of data services directly correlates to the strategy and growth of the business
- Focus on automation use cases, CI/CD approaches and self-service modules relevant for data domains
- Address questions and concerns from downstream data consumers through appropriate channels
- Create data tools for analytics and BI teams that assist them in building and optimizing our product into an innovative industry leader
- Stay up to date with data engineering best practices, patterns, evaluate and analyze new technologies, capabilities, open-source software in context of our data strategy to ensure we are adapting, extending, or replacing our own core technologies to stay ahead of the industry
- Contribute to Analytics engineering process
Minimum Qualifications- Bachelor's degree in computer science, information systems, or a related discipline
- 5+ years in the Data Engineer role
- Built processes supporting data transformation, data structures, metadata, dependency, data quality, and workload management
- Working experience with Snowflake, Hands-on experience with Snowflake utilities, Snow SQL, Snow Pipe. Must have worked on Snowflake Cost optimization scenarios
- Overall solid programming skills, able to write modular, maintainable code, preferably Python & SQL
- Have experience with workflow management solutions like Airflow
- Have experience on Data transformation tools like DBT
- Basic understanding of how to use LLMs for data engineering purposes and tools like GitHub, Copilot, etc.
- Experience working with Git
- Experience working with big data stack environment, like, Hive, Spark and Presto
- Strong analytical, problem solving and interpersonal skills
- Familiar with Scrum
- Ready to work flexible European hours
Preferred Qualifications - Snowflake
- DBT
- Airflow
- CI/CD (Jenkins)
- Basic understanding of Power BI
- AWS environment, for example S3, Lambda, Glue, Cloud watch
- Experience working with remote teams spread across multiple time-zones
- Strong organizational skills and attention to detail
- Have a hunger to learn and the ability to operate in a self-guided manner
This role may require in-person onboarding and/or in-person ID verification.
