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Senior Data Architect

2 days, 12 hours ago
Mexico, Colombia
Senior
Data Architect
Data Science and Analytics
Databricks dbt Feature Engineering Flink GCP Kafka MLOps Snowflake
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Goods & Services

Goods & Services

Goods & Services: We Add Value by creating experiences people love.

Media
51-250
Founded 2016
View All Jobs 18

Description

  • Define and own the enterprise data architecture strategy across core business domains.
  • Establish and govern data standards, naming conventions, schema design principles, and modeling best practices.
  • Lead the design of scalable, reusable data products in semantic and analytical layers.
  • Partner with the Product Data team on shared architectural standards, data contracts, and platform decisions.
  • Evaluate and advise on data platform and tooling choices, including warehouses, lakehouse patterns, orchestration, metadata management, and cataloging.
  • Identify and resolve architectural gaps, redundancy, and data quality risks across the data estate.
  • Develop and maintain a business glossary, data catalog, and enterprise ontology for key domains.
  • Advise Data Science on data availability, feature engineering infrastructure, and model data requirements.
  • Collaborate with Decision Science leadership to ensure analytical models support performance, clarity, and governed self-service.
  • Champion data governance, lineage, and observability as core architectural concerns.

Requirements

  • 5+ years of experience in data architecture, data engineering, or a closely related discipline in a complex, multi-team data environment.
  • Experience designing and governing enterprise data models across transactional, analytical, and semantic layers.
  • Deep expertise with modern data stack patterns, including cloud data warehouses such as Snowflake, BigQuery, or Databricks, as well as lakehouse architectures, dbt, and data cataloging tools.
  • Strong command of data modeling methodologies, including dimensional modeling, Data Vault, and OBT.
  • Experience establishing or evolving data governance programs, including metadata management, lineage, and data quality frameworks.
  • Ability to work across technical and business stakeholders and translate architectural decisions into business value.
  • Experience partnering with Data Science teams on feature engineering, training datasets, or MLOps data infrastructure.
  • Excellent communication and documentation skills for technical and executive audiences.
  • Experience working in matrixed or cross-functional environments without direct authority.
  • Experience in a company with both a centralized data function and an embedded Product Data or Data Platform team (preferred).
  • Familiarity with semantic layer tools such as Cube, MetricFlow, or LookML and headless BI patterns (preferred).
  • Background in data mesh, data product, or federated data governance operating models (preferred).
  • Exposure to real-time or streaming data architecture such as Kafka, Flink, or Spark Streaming (preferred).

Interested in this position?

Apply directly on the company website

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