Staff Data Engineer building scalable pipelines and lakehouse architecture for Sonatype, a software supply chain security company. Driving trusted analytics, ML, and business intelligence data with Databricks, Spark, and modern cloud technologies.
About the role
- Senior Data Engineer at Noda creating scalable data solutions for smarter, sustainable buildings. Collaborating with teams to optimize data for high-performance analytics.
Responsibilities
- Collaborate with technical teams to understand data requirements and deliver data integration solutions.
- Migrate customer data from legacy systems, ensuring data accuracy, consistency, and minimal disruption.
- Perform data modeling, including dimensional modeling, to create structured datasets for analytics and reporting purposes.
- Plan and implement scalable data solutions on cloud platforms such as AWS, Snowflake, and Mongo Atlas.
- Ensure data governance practices are followed to maintain data quality, integrity, and compliance with industry standards.
- Implement data security best practices and ensure compliance with data privacy regulations (e.g., GDPR, CCPA).
- Work in an Agile environment, collaborating with cross-functional teams and using project management tools to deliver projects effectively.
Requirements
- 5–8+ years of experience in Data Engineering, with ownership of production-grade data platforms.
- Proven ability to act as the sole or primary Data Engineer, making architectural decisions, prioritizing work, and setting and meeting delivery timelines without heavy oversight.
- Bachelor’s or Master’s in Computer Science, Data Engineering, or equivalent experience.
- Proven experience managing and optimizing massive datasets (billions of rows / multi-terabyte tables), ensuring high performance and cost-efficiency.
- Deep expertise in Snowflake and MongoDB Atlas (including Federation and CDC) as primary data stores.
- Hands-on experience building real-time ETL/ELT pipelines using Kafka, Kafka Connectors, Estuary.
- Familiarity with Vector Databases and the data infrastructure required to support LLM/RAG applications.
- Proficiency in Python and SQL for data modeling (DBT), query tuning, and general automation.
- Experience with AWS and containerized environments (Docker/Kubernetes).
- A collaborative communicator who is adaptable in a fast-paced DevOps environment.
Benefits
- Healthcare cover, including vision, dental.
- Critical Illness Cover & Life Insurance Policy
- Accidental Death, Dismemberment and Specific Loss
- Long Term Disability Cover
- Pension - Registered Retirement Savings Plan
- Enhanced paternity, maternity and adoption leave.
- Paid personal development days.
- Annual paid volunteer day to help out a charity of your choice
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