Azure Data Architect

Job Title:

About the Role

Data Architect

Key Responsibilities

• Design, build, and govern

  Azure Data Lake/Lakehouse

  on ADLS Gen2 with Databricks/Synapse.
• Implement

  Medallion architecture

  (Bronze/Silver/Gold) for ingestion, refinement, and curated layers.
• Define and lead

  data modeling

  across lakehouse/warehouse (conceptual/logical/physical, star/snowflake, SCDs).
• Architect scalable

  batch and streaming pipelines

  with reliable orchestration.
• Enable GenAI-ready data access through

  Azure AI Search (including vector search)

  and well-structured knowledge datasets.
• Establish standards for

  data quality, security, lineage, cataloging, and access controls

  .
• Partner with AI/ML and BI teams to deliver trusted data products for analytics, forecasting, personalization, and GenAI/RAG applications.
• Mentor data engineers, review designs/code, and ensure best practices for performance and cost.

Required Skills & Experience

• 6+ years

  in data engineering / data architecture roles.
• Strong hands-on experience with

  Azure Data Lake / Lakehouse

  :

• ADLS Gen2

• Azure Databricks and/or Synapse Analytics

• Azure Data Factory (ADF)

  or similar orchestration
• Proven delivery of

  Medallion architecture (Bronze/Silver/Gold)

  .
• Deep expertise in

  data modeling

  and lakehouse/warehouse design:
• dimensional modeling, star schema, normalization/denormalization, SCDs
• Advanced

  SQL

  and strong

  Python/Scala

  for data processing.
• Experience with

  streaming/event-driven pipelines

  :
• Event Hub / Kafka / Service Bus / Structured Streaming
• Hands-on experience with

  PostgreSQL

  (schema design, optimization, integration).
• Strong

  Power BI

  experience:
• semantic modeling, DAX, dashboarding, performance tuning
• Experience with

  Bitbucket

  for source control and CI/CD (pipelines, branching, PR workflow).

• Azure AI Search required

  , including:
• indexing structured/unstructured data
• vector search / hybrid search patterns

• Generative AI enablement exposure on Azure

  , such as:
• preparing data for RAG/knowledge retrieval
• governance of unstructured content for GenAI use
• Expertise in performance tuning, partitioning, and file formats (Delta/Parquet) with cost optimization.
• Strong understanding of

  data governance

  (Purview or equivalent), lineage, RBAC, and PII handling.

Nice to Have

• Experience supporting AI/ML feature stores or model training workloads from lakehouse data.
• Familiarity with LLMOps/GenAI evaluation or prompt-data feedback loops.
• Domain experience in travel/commerce/personalization.

  Role & responsibilities

Preferred candidate profile