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The Senior Solution Architect - Data Platform & Analytics will be responsible for designing and implementing cloud data platforms, primarily using Azure and AWS. The role requires over 8 years of experience in cloud architecture and data governance, with a strong focus on Databricks and analytics solutions. The successful candidate will collaborate with cross-functional teams to ensure robust data ingestion and transformation capabilities.
Job Responsibility:
Lead feature enablement and capability development efforts on Enterprise Data Platform which is based on Databricks lakehouse architecture, including performance and cost optimization
Define reference architectures, engineering standards, and best practices for data lakes, lakehouse patterns, and enterprise analytics
Partner with networking and security teams to design secure connectivity patterns (e.g., private endpoints/links, VNet/VPC integration, routing, firewalling, segmentation) and meet enterprise security standards
Drive architectural governance (design reviews, technology choices, ADRs) and mentor teams to improve delivery quality
Provide guidance to solution architects in designing and architecting scalable and robust cloud-based solutions using Azure or AWS platforms, focusing on big data and analytics
Provide guidance on implementation best practices for data modeling, metadata management, data lineage, and governance in cloud data environments
Collaborate with analytics and reporting teams to integrate solutions with Power BI or similar tools for business insights
Ensure solutions meet high standards of performance, scalability, security, and cost efficiency in cloud environments
Work closely with cross-functional teams including DevOps, product management, and business stakeholders to align on architecture decisions
Stay up to date with trends in cloud, data engineering, analytics, governance, and AI/ML enablement
Requirements:
8+ years of experience designing and implementing cloud data platforms in large enterprises
Strong hands-on cloud solutions and architecture experience with big data platforms such as Databricks
Proven experience delivering data platforms within large enterprises (complex stakeholder environment, governance, security/compliance constraints)
Strong hands-on architecture experience with Databricks (must-have), including Spark and Delta Lake
Expertise in cloud platforms: Microsoft Azure and/or AWS, with working knowledge of core services used in data platforms
Azure networking knowledge (should-have): experience designing/working with private networking, connectivity, and security patterns in Azure
AWS knowledge (should-have): understanding of AWS networking and data services and integration patterns
Experience with Data Lakes, ETL/ELT tools, and distributed processing (Spark)
Experience with reporting/semantic layer tools such as Power BI or Tableau
Hands-on experience with integration/orchestration tools like Azure Data Factory, AWS Glue, FiveTran, and/or Kafka
Knowledge of modern data governance and data management practices (catalog, lineage, data quality, MDM)
Strong problem-solving skills and ability to work in a fast-paced environment
Excellent communication and stakeholder management skills across global teams
Nice to have:
Experience with real-time data streaming and event-driven architecture
Experience with tools such as Databricks, MS Fabric, Azure Data Factory, AWS Glue, Power BI, and Collibra as well as experience with Azure access management and networking