MongoDB Architect or Data Architect (MongoDB/NoSQL

Overview

On Site
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - Long term

Skills

MongoDB

Job Details

Job Title: MongoDB Architect or Data Architect (MongoDB/NoSQL)

Location: Austin, TX (Hybrid)

Duration: Long term

Clients Note:

Need Mongo DB architect

Need candidate who has exp on NoSQL

Knows how to setup mongo DB Cluster

Candidate who can design

Full job description

Client 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.

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) and Oracle is a must
  • 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
  • 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

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
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