Autodesk

Autodesk

Senior Data Engineer

Toronto, ON, CAN · Senior

Sponsorship not specifiedDetected 6 days ago
PythonCode ReviewGitSQLSnowflakeAWSCloud PlatformsTerraformCI/CDJenkinsKafkaSparkAirflowData EngineeringData VisualizationLLMsAgentic AITest AutomationEHR/EMRProblem Solving

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odds of building a lasting career here

38Risky
Cap-exempt (no lottery)0
Sponsors this role85
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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Employer immigration record

from this employer's Department of Labor filings

Green-card filing pattern in this occupation

Context, not a finding about this posting: of this employer's 53 green-card filings in this occupation, 100% were for a worker who already held the job.

Green-card follow-through: 86%

Of 29 labor certifications old enough to have been used, 4 expired without the employer filing the next step. Median time from filing to decision: 483 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.

Reported a layoff in this occupation

In a green-card filing decided 2026-04-17, this employer stated it had laid off workers in Project Management Specialists (CA) during the preceding six months. 3 such filings on record.Describes the period before that filing, not necessarily today. Unlike WARN notices this is occupation-specific and federal.

Files H-1B transfers

12 transfer filings in the last year, covering 12 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • Autodesk is looking for a skilled and innovative Senior Data Engineer to join our Compliance team, which builds data-driven systems to detect and address non-compliant usage of Autodesk software. This is a key strategic initiative that leverages large-scale data processing and analytics to drive business impact.
  • In this role, you will design, build, and optimize scalable data pipelines and distributed processing systems that handle billions of records. You will focus on improving platform reliability, performance, scalability, and operational efficiency while enabling business-critical analytics.

Responsibilities

  • Evaluate and validate AI-generated solutions for correctness, performance, maintainability, and security while following responsible AI practices
  • Design, develop, and optimize large-scale batch and near-real-time data processing pipelines using Apache Spark, PySpark, and Spark SQL
  • Build scalable and efficient ETL/ELT pipelines capable of processing billions of records across distributed data platforms
  • Optimize distributed processing workloads through partitioning, efficient joins, query tuning, resource management, and performance analysis
  • Develop and maintain data processing solutions using technologies such as Hive, Snowflake, AWS S3, EMR, and Glue
  • Build and maintain production-grade data workflows using Apache Airflow, including DAG development, scheduling, dependency management, retries, and failure recovery
  • Implement data quality checks, pipeline monitoring, observability, and alerting to ensure reliable data processing
  • Design reusable, modular, and fault-tolerant pipelines supporting incremental processing, backfills, and operational scalability
  • Develop and maintain scalable, cloud-native data infrastructure on AWS
  • Implement automated testing, version control, code reviews, and software engineering best practices

Requirements

  • 3+ years of hands-on experience with Apache Spark, including PySpark, Spark SQL, and DataFrame APIs
  • 3+ years of strong programming experience in Python and SQL, with demonstrated ability to write clean, modular, maintainable, and testable code
  • Strong understanding of distributed computing fundamentals, including parallel processing, partitioning, shuffling, data skew, fault tolerance, and Spark performance tuning
  • Hands-on experience with Apache Airflow for building, scheduling, and orchestrating complex data pipelines
  • Practical experience using AI-powered coding tools such as GitHub Copilot, Cursor, ChatGPT, Claude, or equivalent solutions in day-to-day software or data engineering development
  • Ability to effectively use AI tools for code generation, debugging, refactoring, testing, and accelerating engineering problem-solving
  • Experience with AWS data services such as S3, EMR, Glue, or equivalent cloud-based data processing platforms
  • Working knowledge of analytical data platforms such as Snowflake, Hive, or Presto/Trino
  • Experience with Git, CI/CD pipelines, and automation tools such as Jenkins
  • Familiarity with data quality frameworks, pipeline observability, production monitoring, and troubleshooting

Nice to have

  • Experience with modern data lake or lakehouse architectures, including Apache Iceberg, Delta Lake, or Apache Hudi
  • Familiarity with streaming data processing technologies such as Apache Kafka or Spark Structured Streaming
  • Experience with Infrastructure as Code tools such as Terraform or AWS CloudFormation
  • Familiarity with LLM APIs, AI agents, or AI-powered workflow automation applied to software or data engineering
  • Experience with BI and analytics platforms such as Power BI or Looker
  • Demonstrated experience improving engineering efficiency, pipeline performance, or cloud infrastructure costs through automation and optimization
  • Welcome to Autodesk!
  • Amazing things are created every day with our software - from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies.

Skills

  • Job Requisition ID #
  • Position Overview
  • Our technology stack includes:

Compensation

  • Salary transparency

Company info

  • We take great pride in our culture here at Autodesk - it's at the core of everything we do.
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This listing is sourced directly from Autodesk's careers page and normalized into a canonical job model.