As a Databricks Solutions Architect Senior Manager, you will lead the design and delivery of modern data platforms that help organizations transform complex data into actionable business insights. You will advise clients on data strategy, cloud migration, data engineering, governance, and analytics, leveraging Databricks technologies to build secure, scalable, and cost-effective solutions. Combining technical expertise with strategic consulting and people leadership, you will oversee project delivery, develop high-performing teams, and cultivate trusted relationships with senior stakeholders. You will also contribute to business development, identify new opportunities, and help organizations maximize the value of their data investments. Working across diverse industries in a collaborative consulting environment, you will have the opportunity to influence enterprise-wide transformation initiatives and advance innovative data solutions. This hybrid position offers a balance of remote work, in-person collaboration, and client engagement.
Lead data architecture and solution design: Design and oversee modern data platforms using Databricks, Lakehouse architecture, medallion design patterns, and relevant cloud technologies. Develop scalable, secure, reliable, and cost-effective architectures aligned with client objectives and established architectural frameworks.
Define and execute data strategies: Work with clients to assess existing on-premises and cloud-based data environments, identify improvement opportunities, and develop roadmaps aligned with organizational priorities. Translate complex technical concepts into clear business recommendations that support strategic decision-making.
Drive data engineering and platform modernization: Lead the design, development, migration, and optimization of data pipelines, ETL processes, data warehouses, databases, and modern data platforms. Oversee data integration, movement, transformation, cleansing, modeling, and analytics to improve performance and business value.
Implement Databricks solutions: Guide the adoption and implementation of Databricks capabilities, including Apache Spark, PySpark, Spark SQL, Delta Lake, Auto Loader, Lakeflow Declarative Pipelines, Databricks SQL, and workflow orchestration. Promote effective development practices, automation, CI/CD, and environment management through Databricks Asset Bundles and Git integration.
Strengthen data governance and security: Establish and implement data governance frameworks, policies, and controls. Leverage Unity Catalog to manage data assets, lineage, access permissions, and data sharing while ensuring appropriate encryption, security, scalability, and operational reliability.
Optimize platform performance and operations: Evaluate and improve data pipelines, queries, models, compute resources, and platform configurations. Oversee solution administration, performance tuning, deployment, monitoring, and cost optimization to ensure sustainable operations.
Lead client engagements and project delivery: Manage engagement teams, project work plans, deliverables, and quality reviews to ensure successful outcomes. Identify and communicate risks, challenges, dependencies, and mitigation strategies to client stakeholders, including senior executives.
Build strong client relationships: Serve as a trusted advisor to clients, understanding their business needs and translating them into practical technology solutions. Communicate the value of Databricks capabilities through compelling data storytelling, presentations, and strategic recommendations.
Develop and mentor high-performing teams: Provide direct supervision, coaching, mentoring, performance evaluations, and professional development opportunities. Foster an inclusive culture of collaboration, open communication, continuous learning, accountability, and high-quality delivery.
Drive business development and market growth: Contribute to proposals, client presentations, solution strategies, and pursuit activities. Identify opportunities to expand existing engagements, develop new client relationships, and integrate complementary technologies and services to enhance consulting capabilities.
Promote innovation and continuous improvement: Stay informed about developments in data engineering, cloud architecture, analytics, machine learning, and generative AI. Evaluate emerging technologies and identify opportunities to improve client outcomes and strengthen data capabilities.