Azure Data Architect

Overview

Remote
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2
Able to Provide Sponsorship

Skills

Azure
Databricks
governance design
metadata
3NF
Canonical
Lakehouse

Job Details

Job Title: Azure Data Architect

Location: Remote (with some Travel to NC, Client will pay for travel)

Duration: 6 to 12 Months

Key Skills: Data Architect Canonical Modelling, Medallion architecture is needed.

We are seeking an experienced Data Architect to lead the design and implementation of a cloud-native data platform leveraging Databricks and Azure. This role is focused on delivering an end-to-end architecture for a high-volume data cleansing and transformation program involving complex source systems and a multi-layered Lakehouse design.

The ideal candidate will bring deep technical expertise in Databricks, Delta Lake, and Azure-native services, with a proven track record of building scalable data platforms from the ground up. This includes designing data ingestion frameworks, modeling clean and curated datasets, enforcing governance and lineage strategies, and enabling downstream analytics and integration.

This is a hands-on leadership role that combines architectural vision with practical implementation guidance, requiring close collaboration with engineers, analysts, QA, and stakeholders across both technical and non-technical domains.

Key Responsibilities

Architectural Leadership

  • Design and assist the implementation of a modern data platform architecture using Databricks, Azure Data Lake, and Delta Lake.
  • Define logical, physical, and semantic data models to support transformation, cleansing, governance, and downstream integration.
  • Guide the architecture of key layers including ingestion, staging, cleansing, curated zones, and reporting-ready datasets.

Platform Ownership

  • Stand up and guide the configuration of a Databricks + Azure environment, including storage, compute, and access layers.
  • Establish architectural standards, naming conventions, reusable patterns, and pipeline frameworks for the platform.
  • Define ingestion strategies for structured and semi-structured data (e.g., VSAM, SQL Server, flat files).
  • Guide and support the implementation of fine-grained access control using Unity Catalog to enable secure data discovery, audit logging, and role-based governance across catalogs, schemas, tables, and columns.
  • Design observability framework leveraging Azure Monitor and Log Analytics to enable platform health monitoring, diagnostics, and alerting.
  • Define credential management strategy using Azure Key Vault to support secure, scalable handling of secrets and configuration values.
  • Establish CI/CD strategy and standards using Azure DevOps Repos and Pipelines, ensuring data workflows and infrastructure components follow controlled, repeatable deployment patterns.

Governance & Metadata

  • Coordinate metadata, access control, and lineage tracking using tools like Unity Catalog and Microsoft Purview.
  • Support data classification, stewardship, and compliance across all layers of the platform.
  • Ensure lineage, auditability, and access controls are enforced consistently across workflows.

Collaboration & Oversight

  • Work closely with Data Engineers and Analysts to translate requirements into scalable architectural components.
  • Review solution designs and implementation plans to ensure consistency with architectural strategy.
  • Provide mentorship and oversight on best practices for data engineering, governance, and observability.

Required Skills & Experience

8+ years in enterprise data architecture or cloud data engineering roles.

Expert-level experience with:
- Databricks, Spark, and Delta Lake, including ACID transactions, time travel, and scalable upsert/merge operations on Azure Data Lake Storage Gen2
- Azure Data Lake Storage, Azure Synapse, and related services

- Performance tuning and job optimization in Spark-based environments (broadcast joins, partitioning, caching)
- Metadata and governance frameworks (Microsoft Purview or equivalent)

Strong understanding of:
- Data modeling techniques (3NF, dimensional, canonical, Lakehouse patterns), Medallion architecture
- Governance, lineage, and compliance strategies for sensitive or regulated data
- Designing fault-tolerant, scalable Azure Data Factory data pipelines for ingestion, transformation, and delivery

Experience architecting solutions with:
- High-volume data cleansing, deduplication, and standardization logic
- Structured and unstructured data sources, including legacy formats
- Parsing EBCDIC/COBOL-formatted VSAM files into structured DataFrames using Spark-Cobol Library in Databricks

Preferred Qualifications:

Experience implementing end-to-end cloud data platforms in Azure + Databricks environments

Background in greenfield implementations where platform setup, governance design, and ingestion strategies are developed from scratch

Relevant certifications such as:
- Azure Solutions Architect Expert
- Databricks Certified Data Engineer Professional

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.