Staff Data Engineer

Навыки

• Avro / Parquet
• AWS
• Azure
• Big Data
• ETL / ELT
• Google Cloud
• HBase / Hive

О компании и продукте

• MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the data platform for the AI era, enabling builders to create, transform, and disrupt industries with software. MongoDB’s unified data platform, the most widely available, globally distributed data platform on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure.
• With offices worldwide and over 67,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.
• Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB.
• To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy , we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB , and help us make an impact on the world!

Задачи

• Guide the Data Engineering team on building highly performance ETL pipelines using Spark and other Big Data technologies
• Help design the architecture of our Internal Data Platform to support the implementation of a robust medallion architecture
• Provide thought leadership on ways to achieve infrastructure cost savings on Cloud hyperscalers
• Design and build AI agents that can help automate many of the common development and support tasks that the team performs
• Work with Security and Compliance teams to ensure that datasets have appropriate permissions and regulations in place
• Work with our Data Platform, and Governance sibling teams to make data scalable, consumable, and discoverable
• We’re looking for someone with
• 5+ years of Spark and Python experience
• Thorough AI knowledge, particularly with codegen tools and agentic frameworks
• Hive, Iceberg, Glue, or other technologies that expose big data as tables
• Familiarity with different big data file types such as Parquet, Avro, and JSON
• Exposure to real-time or streaming data technologies is a plus
• Success Measures
• In 3 months, you'll have a thorough understanding of the architecture of MongoDB’s internal Data and AI ecosystem
• In 6 months, you'll have owned the delivery of a large project from start (scoping, design) to finish (delivery)
• In 12 months, you'll have designed new features, led development work, and become a go-to expert on parts of the system

Требования

• 10+ years experience working on enterprise data lakes/warehouses
• 5+ years of direct hands-on experience working with AWS or GCP

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