DATA ARCHITECT

Jobleads-US; San Francisco (CA); Remote; USD 120,000 - 160,000; Full time

Job summary

A leading company is seeking a Data Architect to oversee data management and governance across the organization. The role involves designing data models, ensuring data accuracy, and implementing data security standards. Ideal candidates will have strong SQL skills, cloud data warehousing experience, and a customer-focused approach.

Qualifications

• At least 3 years experience building data models for structured and semi-structured data.
• Highly proficient in SQL; MQL knowledge is a plus.
• Experience with distributed query engines like Trino or BigQuery.

Responsibilities

• Design data models and schemas for the internal data lake and warehouse.
• Create and execute test plans ensuring data accuracy and performance.
• Document metadata and promote self-service data discovery.

Skills

SQL

Data Modeling

Data Governance

Customer Focus

Python

Tools

MongoDB Query Language

Distributed Query Engines

Cloud-Based Data Warehouses

Job description

MongoDBs mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. We enable organizations of all sizes to easily build, scale, and run modern applications by helping them modernize legacy workloads, embrace innovation, and unleash AI. Our industry-leading developer data platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available in more than 115 regions across AWS, Google Cloud, and Microsoft Azure. Atlas allows customers to build and run applications anywhereon premises, or across cloud providers. With offices worldwide and over 175,000 new developers signing up to use MongoDB every month, its no wonder that leading organizations, like Samsung and Toyota, trust MongoDB to build next-generation, AI-powered applications.

MongoDB is growing rapidly and seeking a Data Architect to be a key member of a growing Data Architecture team; overseeing the governance, management and stewardship of data across the organization. As a Data Architect, you will be the bridge between the business and data engineering teams. You will design data models and schemas to produce high-performing, curated datasets in a mixed SQL and NoSQL environment, and drive the implementation to completion. You will populate an enterprise data catalog with key technical and business metadata driving data discoverability, and facilitate the adoption of enterprise data governance policies and procedures.

This role will be based remotely in Austin, New York City, Seattle, or California.

Who? At least 3 years experience building data models to support structured and semi-structured product data including telemetry

Highly proficient in SQL. MQL (MongoDB Query Language) knowledge is a plus

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

Familiarity with Python and rudimentary Prompt Engineering

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

What? As a Data Architect, you will :

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

Success Measures In 3 months, youll have fully ramped with our Business and Data teams

In 6 months, youll have delivered at least one fully documented data model that provides value to the business

In 12 months, youll have delivered multiple data models across a variety of use cases, and are comfortable working with all aspects of our internal data platform

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