Job Title : Sr. Databricks Lead/Architect
Location: Boston MA (5 days onsite)
Duration: 12 Months
Key Responsibilities
Stakeholder Engagement & Solution Leadership
-
Act as the primary technical liaison between business stakeholders and engineering teams.
-
Lead requirement discovery sessions and translate business needs into scalable data architecture solutions.
-
Present architecture approaches trade-offs and roadmaps to leadership and decision-makers.
-
Provide technical leadership across design implementation and major delivery milestones.
-
Collaborate with distributed and offshore teams to ensure alignment and quality execution.
Data & Platform Architecture
-
Design and implement end-to-end Azure-based data platforms leveraging Azure Databricks and Azure Data Lake.
-
Define and implement lakehouse architecture patterns supporting batch streaming and near real-time processing.
-
Establish data modeling standards including layered architecture (bronze/silver/gold) and curated data models.
-
Design integration patterns with upstream and downstream systems including APIs event streaming platforms and analytics tools.
-
Support cloud modernization and legacy platform transformation initiatives.
-
Ensure data governance security scalability and cost optimization best practices are applied.
Technical Governance & Delivery Oversight
-
Review and validate development deliverables to ensure adherence to architecture standards.
-
Provide guidance on Spark performance optimization data engineering best practices and reusable framework design.
-
Establish CI/CD processes and DevOps enablement using Azure DevOps and Git.
-
Implement monitoring logging and performance optimization strategies across the data platform.
-
Drive continuous improvement in architecture performance and cost efficiency.
Required Technical Skills
-
Strong hands-on expertise in Azure Databricks (Spark Delta Lake Unity Catalog).
-
Deep experience with:
-
Azure Data Lake Storage (ADLS Gen2)
-
Azure Data Factory or Synapse Pipelines
-
Event-driven or streaming architectures (Kafka Event Hub Structured Streaming)
-
Python SQL Spark optimization techniques
-
Solid understanding of modern data warehousing and lakehouse architectures.
-
Experience integrating BI tools such as Power BI or similar analytics platforms.
-
Exposure to ML/AI integration within Databricks environments is a plus.
Experience & Qualifications
-
10 years of experience in data engineering or data architecture roles.
-
5 years designing and implementing solutions on Azure data platforms.
-
3 years in a technical lead or solution architect capacity.
-
Azure and/or Databricks certifications preferred.
Job Title : Sr. Databricks Lead/Architect Location: Boston MA (5 days onsite) Duration: 12 Months Key Responsibilities Stakeholder Engagement & Solution Leadership Act as the primary technical liaison between business stakeholders and engineering teams. Lead requirement discovery sessions...
Job Title : Sr. Databricks Lead/Architect
Location: Boston MA (5 days onsite)
Duration: 12 Months
Key Responsibilities
Stakeholder Engagement & Solution Leadership
-
Act as the primary technical liaison between business stakeholders and engineering teams.
-
Lead requirement discovery sessions and translate business needs into scalable data architecture solutions.
-
Present architecture approaches trade-offs and roadmaps to leadership and decision-makers.
-
Provide technical leadership across design implementation and major delivery milestones.
-
Collaborate with distributed and offshore teams to ensure alignment and quality execution.
Data & Platform Architecture
-
Design and implement end-to-end Azure-based data platforms leveraging Azure Databricks and Azure Data Lake.
-
Define and implement lakehouse architecture patterns supporting batch streaming and near real-time processing.
-
Establish data modeling standards including layered architecture (bronze/silver/gold) and curated data models.
-
Design integration patterns with upstream and downstream systems including APIs event streaming platforms and analytics tools.
-
Support cloud modernization and legacy platform transformation initiatives.
-
Ensure data governance security scalability and cost optimization best practices are applied.
Technical Governance & Delivery Oversight
-
Review and validate development deliverables to ensure adherence to architecture standards.
-
Provide guidance on Spark performance optimization data engineering best practices and reusable framework design.
-
Establish CI/CD processes and DevOps enablement using Azure DevOps and Git.
-
Implement monitoring logging and performance optimization strategies across the data platform.
-
Drive continuous improvement in architecture performance and cost efficiency.
Required Technical Skills
-
Strong hands-on expertise in Azure Databricks (Spark Delta Lake Unity Catalog).
-
Deep experience with:
-
Azure Data Lake Storage (ADLS Gen2)
-
Azure Data Factory or Synapse Pipelines
-
Event-driven or streaming architectures (Kafka Event Hub Structured Streaming)
-
Python SQL Spark optimization techniques
-
Solid understanding of modern data warehousing and lakehouse architectures.
-
Experience integrating BI tools such as Power BI or similar analytics platforms.
-
Exposure to ML/AI integration within Databricks environments is a plus.
Experience & Qualifications
-
10 years of experience in data engineering or data architecture roles.
-
5 years designing and implementing solutions on Azure data platforms.
-
3 years in a technical lead or solution architect capacity.
-
Azure and/or Databricks certifications preferred.
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