Position Overview
Autodesk has invested in data-driven decision-making, optimizing our platform’s 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 Manager, Data Enablement 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. As part of the Analytics & Insights (A&I) team, you will play a critical role in enabling data-driven decision-making by building and maintaining trusted data pipelines, curated data models and analytics-ready datasets.
You will work closely with analysts, data scientists, Fin Ops developers and product teams to build solutions that support reporting, experimentation, and advanced analytics at scale.
Preference for candidates in Toronto or Montreal, Canada.
Responsibilities
Lead and mentor a team of data developers 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, Fin Ops developers, 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 team’s capabilities and toolset
Minimum Qualifications
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
Preferred Qualifications
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 Fin Ops 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
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Description du poste
Autodesk a investi dans la prise de décision basée sur les données, optimisant ainsi les activités, les produits et les coûts de notre plateforme. Les cinq prochaines années vont transformer notre façon de travailler, avec une augmentation considérable du volume de données et une expansion de l'IA/ML afin d'offrir encore plus de valeur à nos clients.
Sous la responsabilité du directeur Insights and Analytics, le responsable Data Enablement constituera…
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