Job Title

Autodesk has invested in data-driven decision-making, optimizing our platforms business, product, and cost. The next five years will transform how we work, with a surge in data volume and scaling of AI/ML to provide even greater value to our customers. Reporting to the Director, Insights and Analytics, the Data Engineering Manager will build and lead a team focused on building scalable, reliable, and high-quality data pipelines and processes that power strategic analytics, data science and cost optimization activities across Autodesk''''s platform initiatives.* Lead and mentor a team of data engineers responsible for developing and maintaining data pipelines and infrastructure on platforms such as AWS and Snowflake* Define and drive the long-term vision for data engineering in alignment with Autodesk data platform strategy and analytics roadmap* Partner with analysts, data scientists, FinOps engineers, engineering and product teams to understand data needs and translate them into scalable data solutions* Establish clear standards for operational excellence and define what good looks like across all stages of the data lifecycle* Drive the design and development of data models and ETL/ELT processes that ensure high data quality, availability, and performance* Champion and implement data engineering best practices, including testing, documentation, governance, and observability* Leverage AI-driven approaches in data workflows, including anomaly detection, orchestration optimization, and automated code generation* Manage project timelines, resources, and priorities across multiple initiatives in a fast-paced, cross-functional environment* Stay current with emerging trends in data engineering and proactively evolve the teams capabilities and toolset* 10 years of experience in data engineering, with at least 4 years in a leadership or management role* Demonstrated success leading technical teams and delivering complex data engineering projects* Experience working with cloud data platforms (e.g., AWS, Snowflake, Databricks) and orchestration tools (e.g., Airflow)* Proficient in SQL, Python, and data modeling best practices* Knowledge of big data processing frameworks (e.g. Spark, Hadoop)* Experience building and maintaining large-scale batch and real-time data pipelines* Experience with both ETL and ELT pipelines, including traditional ETL tools (e.g., Airflow, Informatica) and modern ELT frameworks (e.g., dbt, Snowflake)* Excellent communication and stakeholder management skills* Drive scalable architecture through platform systems design and modern design patterns* Experience working in product/platform organizations or supporting data engineering for SaaS-based applications* Familiarity with data quality frameworks, observability tools, and CI/CD for data* Knowledge of FinOps practices, data security, and compliance in cloud environments* Knowledge of AWS IAM roles, permissions, and best practices for least-privilege access* Passion for coaching talent and building inclusive, high-performing teams* 10 ans d''''exprience en ingnierie des donnes, dont au moins 4 ans dans un rle de direction ou de gestion* Exprience avre dans la direction d''''quipes techniques et la ralisation de projets complexes d''''ingnierie des donnes* Exprience de travail avec des plateformes de donnes cloud (par exemple, AWS, Snowflake, Databricks) et des outils d''''orchestration (par exemple, Airflow)* Matrise de SQL, Python et des meilleures pratiques en matire de modlisation des donnes* Connaissance des cadres de traitement des mgadonnes (par exemple, Spark, Hadoop)* Exprience dans la cration et la maintenance de pipelines de donnes grande chelle, par lots et en temps rel* Exprience avec les pipelines ETL et ELT, y compris les outils ETL traditionnels (par exemple, Airflow, Informatica) et les cadres ELT modernes (par exemple, dbt, Snowflake)* Excellentes comptences en communication et en gestion des parties prenantes* Capacit mettre en uvre une architecture volutive grce la conception de systmes de plateformes et des modles de conception modernes* Exprience dans des organisations de produits/plateformes ou dans le soutien l''''ingnierie des donnes pour des applications SaaS* Connaissance des cadres de qualit des donnes, des outils d''''observabilit et du CI/CD pour les donnes* Connaissance des pratiques FinOps, de la scurit des donnes et de la conformit dans les environnements cloud* Connaissance des rles, des autorisations et des meilleures pratiques AWS IAM pour un accs avec le moins de privilges possible* Passion pour l''''accompagnement des talents et la constitution d''''quipes inclusives et performantes #J-18808-Ljbffr