Senior Data Architect

Posted 20hrs ago

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Job Description

Senior Data Architect at Blanc Labs responsible for designing enterprise data architecture strategies. Leading the implementation of AI-enabled data ecosystems across modern data platforms.

Responsibilities:

  • Design and evolve enterprise data architecture strategies, including data models, data lakes, and data warehouses
  • Lead the design and implementation of ETL/ELT pipelines to support analytics, reporting, and AI/ML workloads
  • Architect and implement Master Data Management (MDM) frameworks to ensure data quality, consistency, and governance across systems
  • Design and build modern data platforms using Databricks and Microsoft Fabric
  • Architect cloud-native data solutions on AWS, ensuring scalability, security, and cost efficiency
  • Define data governance standards, metadata management practices, and data lineage frameworks
  • Collaborate with data science and AI teams to design data architectures that support machine learning, GenAI, and agentic system use cases
  • Partner with business and technical stakeholders to translate data requirements into scalable architectural solutions
  • Evaluate and recommend tools, technologies, and best practices for data integration, storage, and processing
  • Provide technical leadership and mentorship to data engineering teams
  • Troubleshoot complex data pipeline and platform issues, driving root cause analysis and long-term fixes
  • Drive continuous improvement in data architecture, performance, and observability

Requirements:

  • 8+ years of experience in data architecture, data engineering, or related roles
  • Strong hands-on experience designing data models (conceptual, logical, physical) for enterprise systems
  • Proven experience building and optimizing ETL/ELT pipelines
  • Hands-on experience implementing Master Data Management (MDM) solutions
  • Strong expertise with Databricks for data engineering and analytics workloads
  • Experience with Microsoft Fabric for unified data and analytics solutions
  • Solid experience with AWS data services (e.g., S3, Glue, Redshift, RDS, Lake Formation)
  • Understanding of AI/ML data requirements, including feature engineering and data preparation for GenAI and LLM-based systems
  • Strong knowledge of data governance, data quality, and metadata management practices
  • Proficiency in SQL and familiarity with Python or other data engineering languages
  • Strong analytical and problem-solving skills, with the ability to communicate technical concepts to non-technical stakeholders.

Benefits:

  • Accommodations within reason due to a disability or medical need are available on request for candidates taking part in the recruitment process