This role pays more than
89%
of similar roles. Most pay
$153,287–$225,000
— the shaded band above.
At the midpoint, this role pays about
$263k
versus about
$189k
for comparable roles.
Based on 240 similar postings.
Employer
About MongoDB
MongoDB is a leading American software company that develops and provides commercial support for a popular, source-available document database. Designed to handle unstructured and structured data natively, its platform is purpose-built for modern cloud applications, analytics, and AI experiences.
MongoDB currently has
311 open roles
on FindRole.
Listed pay typically runs
$126,000–$226,000
across 95 roles with salary data.
Senior Staff Enterprise Architect, Data leads the strategy, design, and modernization of the enterprise data landscape at the intersection of architecture, engineering, and AI enablement. The role involves designing semantic layer architectures, establishing Master Data Management for customer and product domains, and developing cross-cloud integration strategies to unify Data Lakes and Warehouses across multi-cloud platforms. Key responsibilities include building automated data quality frameworks, defining lineage requirements for financial and AI datasets, and evaluating AI-powered tools for observability and security. The position requires expertise in SQL, Python, and modern platforms like Snowflake or Databricks, with specific experience in RAG architectures and vector databases. This role solves complex problems regarding data latency, governance, and self-service access while ensuring high-quality, governed data feeds into AI models through robust infrastructure and standardized technical patterns.
Design and implement a semantic layer to standardize business metrics and enable natural language queries.
Develop Master Data Management strategies for Customer, Product, Finance, and People domains.
Architect cross-cloud data integration patterns to balance performance, cost, and data freshness across multi-cloud platforms.
Evaluate and implement AI-powered tools for automated data quality monitoring and security classification.
Design high-performance data ingestion architectures using CDC and real-time streaming to reduce data latency.
Lead "build vs. buy" evaluations and conduct TCO analyses for data platform, ETL, and master data tooling.
Establish comprehensive data lineage frameworks to ensure compliance with regulatory requirements like SOX and GDPR.
Mentor a team of engineers and architects while leading an architecture community of practice.
What we're looking for
Must have 12+ years of experience in IT with at least 7 years in Data Architecture, Data Engineering, or Enterprise Architecture roles.
Must have 10+ years of experience across three or more areas: data architecture, data engineering, database management, analytics, or cloud infrastructure.
Must possess a Bachelor's degree in computer science, computer engineering, electrical engineering, systems analysis, or a related field; an MS or advanced degree is preferred.
Proven ability to architect solutions bridging Data Lakes and Warehouses across multi-cloud platforms like AWS, Azure, and Google Cloud.
Hands-on experience with Master Data and data lineage tools, including designing models for at least two domains (Customer, Product, Finance, or People).
Experience implementing AI/ML tools for data quality monitoring, automated data classification, and RAG architectures using vector databases.
Proven success reducing data latency using CDC, streaming, or real-time integration patterns.
Proficiency in SQL and Python with experience in modern data platforms such as Snowflake, Databricks, or BigQuery.
Data Modeling
SQL
Python
AWS
S3
Glue
Redshift
Athena
Lake Formation
ETL
ELT
Data Governance
Data Quality
Metadata Management
Data Cataloging
Lineage
Agile
Data Architecture
Python
SQL
AWS
S3
Glue
Redshift
Athena
Lake Formation
dbt
Airflow
ETL
ELT
Data Modeling
Data Governance
Metadata Management
Data Cataloging
Agile
Databricks
Delta Lake
Unity Catalog
AWS
Python
Java
SQL
NoSQL
Data Engineering
Data Modeling
Machine Learning
Data Governance
Fivetran
HVR
Vault
Data Observability