Data Engineer

Position Overview

We are looking for an exceptional 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 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 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 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
• Build and maintain data quality and durability tracking mechanisms to provide visibility into and address inevitable changes in data ingestion, processing, and storage
• Translate technical designs into business appropriate representations and 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 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
• 3+ years in the Data Engineer role
• Built processes supporting data transformation, data structures, metadata, dependency, data quality, and workload management
• 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 transformations tools like DBT
• Experience working with Git
• Experience working with big data 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
• Fivetran
• Airflow
• CI/CD (Jenkins)
• Basic understanding of Power BI
• AWS environment, for example S3, Lambda, Glue, Cloud watch
• Basic understanding of Salesforce
• Experience working with remote teams spread across multiple time-zones
• Attention to detail
• Have a hunger to learn and the ability to operate in a self-guided manner