Key skills
PythonJavaScalaSQLMySQLPostgreSQLMongoDBCassandraData modelingData architectureETL processesKafkaFlinkParquetIcebergApache AirflowAWSAzureGoogle CloudAWS GlueAWS EMRAWS RedshiftAWS S3BigQuerySnowflakeGitCI/CD pipelinesNoSQLMachine LearningETLData EngineeringData WarehousingAnalyticsRedshiftAirflowKubernetesDockerS3GlueVersion ControlCI/CD
About this role
Autodesk is a company that creates innovative software for various industries. They are seeking a Data Engineer to design and maintain scalable data pipelines, collaborating with multiple teams to support business needs and strategic initiatives.
Responsibilities:
- Design, build, and maintain scalable data pipelines that support continuous data flow, analytics, and machine learning use cases
- Develop and implement data models and schemas to ensure data integrity, accessibility, and usability
- Manage and optimize relational and NoSQL database systems for performance and availability
- Integrate data from multiple sources while ensuring consistency, quality, and reliability
- Design and manage ETL processes to move and transform data across systems
- Implement data governance practices to support data security, privacy, and compliance
- Collaborate with data scientists, machine learning engineers, analysts, platform engineers, and business stakeholders to understand requirements and deliver effective solutions
- Tune database and pipeline performance for efficient processing and querying of large datasets
- Maintain clear documentation for data processes, models, architecture, and operational workflows
- Partner with internal platform teams to build reliable, scalable, and reusable data solutions
Requirements:
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience
- Experience programming in Python, Java, Scala, or a similar language
- Strong SQL skills and experience working with relational databases such as MySQL or PostgreSQL
- Experience with NoSQL databases such as MongoDB, Cassandra, or similar technologies
- Understanding of data modeling, data architecture, and ETL processes
- Experience with big data technologies and frameworks such as Kafka, Flink, Parquet, Iceberg, or similar tools
- Experience using workflow orchestration or ETL tools such as Apache Airflow
- Experience with cloud platforms such as AWS, Azure, or Google Cloud
- Familiarity with cloud data services such as AWS Glue, EMR, Redshift, S3, BigQuery, or similar
- Experience with data warehousing solutions such as Snowflake, Redshift, or BigQuery
- Experience with version control systems such as Git and CI/CD pipelines
- Experience in customer journey analytics, personalization, or digital conversion optimization
- Familiarity with machine learning concepts and experience collaborating with data science or machine learning teams
- Knowledge of real-time data processing and streaming architectures
- Experience with Docker, Kubernetes, or other containerization and orchestration technologies
- Relevant certifications in big data technologies, cloud platforms, or database management
- Master's degree in Computer Science, Data Engineering, Information Technology, or a related field