Senior Data Developer

Job Requisition ID #

25WD90544

Position Overview:

Data Engineers will be responsible for designing, building, maintaining, monitoring, integrating, and testing scalable data pipelines in production. You will partner with multi-disciplinary teams such as Machine Learning Engineering, Platform Engineering, Data Analysts on coordinating delivery of pipelines for specific business needs. Your work will contribute to strategic initiatives such as optimization of digital conversion metrics and development of Autodesk Assistant, an LLM-driven chatbot intended to answer customer inquiries.

Our team culture is built on collaboration, mutual support, and continuous learning. We emphasize an agile, hands-on, and technical approach at all levels of the team. As a group, we want to continuously improve our work as well as our knowledge of trends and techniques relevant to our areas. We encourage personal development and knowledge sharing.

Key Responsibilities:

• Data Pipeline Construction: Design, build, and maintain scalable data pipelines to support continuous data flow and analytics
• Data Modeling: Develop and implement effective data models and schemas to ensure data integrity and accessibility
• Database Management: Oversee and optimize database systems (SQL, NoSQL) ensuring high performance and availability
• Data Integration: Integrate data from various sources, ensuring consistency, quality, and reliability
• ETL Processes: Design and manage Extract, Transform, Load (ETL) processes to move data between systems
• Data Governance: Implement and enforce data governance policies to ensure data security, privacy, and compliance
• Collaboration: Work closely with data scientists, analysts, and stakeholders to understand data requirements and deliver solutions
• Performance Tuning: Enhance and tune database performance for efficient processing and querying of large datasets
• Documentation: Maintain comprehensive documentation for data processes, models, and architecture
• Platform Mindset: Partner with internal platform team on the following tasks
• Provide technical leadership and mentorship for less-experienced members of the team
• Demonstrate experience working in cross-functional teams to deliver data engineering solutions in production

Minimum Qualifications:

• Proficiency in programming languages such as Python, Java, or Scala
• Strong knowledge of SQL and experience with relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra)
• Knowledge of big data technologies and frameworks (e.g., Kafka, Flink, Parquet, Iceberg, etc)
• ETL Tools: Skilled in using ETL tools like Apache Airflow
• Experience with cloud services from AWS, Azure, or Google Cloud, including data-related services like AWS Glue, EMR, Redshift, and S3
• Experience with data warehousing solutions like Snowflake, Redshift, or BigQuery
• Understanding of data modeling, data architecture, and ETL processes
• Experience with version control systems (e.g., Git) and continuous integration/continuous deployment pipelines
• Bachelor's degree in computer science, Information Technology, or a related field. A master's degree is a plus
• Relevant certifications in big data technologies, cloud platforms, or database management are a plus

Preferred Skills:

• Experience in customer journey analytics and personalization
• Familiarity with machine learning concepts and collaboration with data science teams
• Knowledge of real-time data processing and streaming architectures
• Experience with containerization tools like Docker and orchestration platforms like Kubernetes