Senior Data Specialist

Summary

Join Brillio as a Senior Data Specialist and lead platform design and architecture for the data management system using Databricks on Azure. Collaborate with Microsoft engineers and internal stakeholders to develop and enforce data governance standards. Coordinate with Subject Matter Experts (SMEs) to define and maintain trusted data assets. Drive data quality initiatives and enable advanced analytics use cases, including AI/ML model development and self-healing mechanisms. Work cross-functionally with IT, Engineering, and Business teams to integrate data sources. Identify and resolve data bottlenecks, and partner with Microsoft to stay aligned on joint architecture and roadmap. This remote opportunity requires 8+ years of experience in data management and 3+ years of hands-on experience with Databricks, Spark, and the Azure data ecosystem.

Requirements

• 8+ years of experience in data management, data engineering, or platform architecture
• 3+ years of hands-on experience with Databricks, Spark, and the Azure data ecosystem (e.g., Azure Data Lake, Synapse, ADF)
• Strong background in data quality frameworks, data governance, and metadata management
• Experience in designing enterprise data platforms and leading cross-functional data initiatives
• Deep understanding of ETL/ELT pipelines, data modeling, and data integration strategies
• Proven track record in working with business SMEs to translate data requirements into actionable solutions
• Excellent stakeholder communication and strategic partnership management skills

Responsibilities

• Lead platform design and architecture for the data management system using Databricks on Azure in collaboration with Microsoft engineers and internal stakeholders
• Develop and enforce data governance standards, including standardized definitions, data catalogs, metadata, and lineage
• Coordinate with Subject Matter Experts (SMEs) to define, validate, and maintain trusted data assets
• Drive data quality initiatives by implementing validation, profiling, and cleansing frameworks across data sources
• Enable advanced analytics use cases, including: AI/ML model development for proactive issue detection Self-healing mechanisms for IT operations Digital experience optimization via experimentation and telemetry
• Work cross-functionally with IT, Engineering, and Business teams to integrate and aggregate disparate data sources into a unified model
• Identify and resolve data bottlenecks, improve data accessibility, and eliminate inefficiencies in the current ecosystem
• Partner with Microsoft to stay aligned on joint architecture, tools, and roadmap

Preferred Qualifications

• Experience working on AI/ML-enablement or self-healing IT systems
• Knowledge of IT operations data, telemetry, or digital experience platforms
• Familiarity with controlled experimentation platforms or A/B testing methodologies
• Microsoft or Databricks certifications (e.g., DP-203, Databricks Data Engineer)