Autodesk
SeniorDataDeveloper,Analytics&Insights
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“Senior Data Developer, Analytics & Insights at Autodesk. Skills: Data pipelines, Data engineering, Cloud data platforms, AI-driven tasks. Design ELT/ETL data pipelines. Develop ELT/ETL data pipelines”
Industry & Context.
Problem solver
What They're Looking For.
Must Have
5+ years data processing, 5+ years data engineering, AWS experience required, Hands-on software development Python, Expert understanding SQL, Expert understanding dimensional modeling, Expert understanding analytical data warehouses, Knowledge of big data processing frameworks, Expertise with data pipeline orchestration tools, Familiar with processing semi-structured file formats, Bachelor’s degree computer science, Bachelor’s degree data science
Nice to Have
Experience with Jinja, Experience with Shell scripting, Experience with DBT, Experience with Spark SQL, Experience developing in Cloud platform serverless technologies, Experience with remote development AWS SDK, Experience with ETL and ELT pipelines, Knowledge of AWS IAM roles, Knowledge of AWS IAM permissions, Knowledge of AWS IAM best practices, Experience with Terraform AWS resource provisioning, Experience with Terraform remote state management, Experience with Terraform security best practices, Hands-on experience AWS networking, REST API design, REST API implementation, Familiarity with containers, Familiarity with infrastructure-as-code principles, Experience with automation frameworks, Master’s degree computer science, Master’s degree data science, Experience with AI-native data engineering technologies, Demonstrated ability structure data AI reasoning, Experience reducing latency agentic workflows
What You'll Do.
Design ELT/ETL data pipelines
Develop ELT/ETL data pipelines
Automate ELT/ETL data pipelines
Maintain ELT/ETL data pipelines
Maintain data architecture
Enhance data architecture
Interface with data peers
Interface with product managers
Interface with cross-functional stakeholders
Document technical solutions
Implement best practices data quality
Implement best practices data integrity
Implement best practices data governance
Monitor data processes
Validate data processes
Apply AI-native data engineering mindset
Use ML-driven validation
Use anomaly detection
Use automated schema evolution
Use automated data lineage
Optimize pipeline performance
Optimize resource efficiency
How You'll Work.
Team & Collaboration
Collaborate with analysts; Collaborate with data scientists; Collaborate with stakeholders; Collaborate with Data Engineering teams; Interface with data peers; Interface with product managers; Interface with cross-functional stakeholders
Communication Scope
Written communication; Interpersonal communication
Full Job Description
**Job Requisition ID #** 26WD98881 _L 'affichage de poste en français suivra / The French job posting follows_ **26WD98881, Senior Data Developer, Analytics & Insights** **Position Overview** Autodesk is looking for a talented and motivated Senior Data Developer to join our Platform Strategy & Emerging Technologies (PSET) organization to develop robust and scalable data pipelines using and improving existing platforms, to support data-driven decision-making across the platform initiatives. The successful candidate will drive performance enhancements, build pipelines, and collaborate with analysts, data scientists, stakeholders and other Data Engineering teams across Autodesk. You will work with cutting edge technologies in the big data space. **Responsibilities** * 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 **Minimum Qualifications** * 5+ years of data processing and data engineering experience in a fast-paced, large cloud-based infrastructure (AWS experience required) * Hands-on softwa
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