Data Architect

Summary

Join MongoDB's growing Data Architecture team as a Data Architect, bridging the gap between business and data engineering. You will design and implement high-performing data models in a mixed SQL and NoSQL environment, populate an enterprise data catalog, and drive the adoption of data governance policies. This remote U.S.-based role requires at least 3 years of experience building data models for structured and semi-structured data, proficiency in SQL, and experience with distributed query engines. You will partner with stakeholders, validate data, design schemas, create test plans, implement data security, and document metadata. MongoDB offers a competitive salary, benefits including flexible paid time off and generous parental leave, and a supportive culture.

Requirements

• At least 3 years experience building data models to support structured and semi-structured product data including telemetry
• Highly proficient in SQL
• Experienced with at least one distributed query engine or cloud-based data warehouse, such as Trino or BigQuery
• Customer focused, understanding that delivering business value is of utmost importance
• Skilled at eliciting requirements and communicating across a diverse set of engineers and partners
• Well-versed in core data lake, data warehousing and data security concepts
• Familiar with data catalog functionality, business glossaries, metadata management and data lineage
• Familiar with cloud computing concepts and big data storage formats such as Parquet and Iceberg
• Capable of juggling multiple projects simultaneously
• A lifelong learner who strives for continuous improvement

Responsibilities

• Partner with Product Owners and other Stakeholders to document data requirements, utilizing your experience to provide insights and add value to the process
• Validate and assess incoming product telemetry data, ensuring alignment with documentation and meeting Product Owners and other Stakeholders' expectations by thorough cross-referencing and testing
• Design data models and schemas within the internal data lake and data warehouse that will be used for analytical and data science consumption
• Create and execute test plans to ensure data is accurate and performance meets SLAs
• Scope and create SQL-based pipelines prioritizing data consistency and accuracy
• Implement data security standards for data access
• Document metadata and lineage in the enterprise data catalog, promoting self-service data discovery and exploration

Preferred Qualifications

• MQL (MongoDB Query Language) knowledge
• Familiarity with Python and rudimentary Prompt Engineering

Benefits

• Flexible paid time off
• 20 weeks fully-paid gender-neutral parental leave
• Fertility and adoption assistance
• 401(k) plan
• Mental health counseling
• Access to transgender-inclusive health insurance coverage
• Health benefits offerings