Senior Data Developer, Analytics & Insights

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Autodesk

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1982

📱 Media

Architecture • Engineering • Media

Autodesk is a global leader in software for designers, engineers, builders, and creators. The company provides a comprehensive suite of design and engineering applications including popular products like AutoCAD, Revit, and 3ds Max. Through its Design and Make Platform, Autodesk empowers professionals across various industries to design, visualize, and manage projects efficiently, facilitating innovation and sustainability in architecture, engineering, construction, and manufacturing.

📋 Description

• Design, develop, automate and maintain scalable, robust and reliable ELT/ETL data pipelines that collect, process and transform large volumes of structure and unstructured data from various sources • Maintain and enhance our existing data architecture to ensure smooth and efficient data flow across platforms • Interface with data peers, product managers and cross-functional stakeholders to gather requirements, sequence work, and document technical solutions • Implement best practices for data quality, integrity and governance, including monitoring, validation and auditing processes to ensure reliable and consistent data availability • Contribute to a team culture that values quality, robustness, and scalability while fostering initiatives and innovation by staying up to date with industry trends and new technologies • Apply an AI-native data engineering mindset by using ML-driven validation, anomaly detection, automated schema evolution, automated data lineage and optimizations for pipeline performance and resource efficiency

🎯 Requirements

• 5+ years of data processing and data engineering experience in a fast-paced, large cloud-based infrastructure (AWS experience required) • Hands-on software development experience in Python • Expert understanding of SQL, dimensional modeling, and analytical data warehouses, such as Snowflake, Presto/Hive • Understanding of Data Engineering best practices for medium to large scale production workloads • Knowledge of big data processing frameworks (e.g. Spark, Hadoop) • Expertise with data pipeline orchestration tools, such as Airflow • Familiar with processing semi-structured file formats such as Json or parquet • Bachelor’s degree in computer science, data science, or related fields

🏖️ Benefits

• Annual cash bonuses • Comprehensive benefits package