Databricks Solutions Architect Senior Manager

Accountabilities:

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.
Requirements:
Education: Bachelor's degree in Management Information Systems, Computer Information Systems, Analytics, or another relevant discipline.
Professional experience: At least 7 years of experience in professional services, technology consulting, data engineering, or a related industry.
Databricks certification: Required professional certification as a Databricks Certified Data Engineer Professional or Databricks Certified Machine Learning Professional. Databricks Champion status is preferred.
Data architecture expertise: Demonstrated experience designing modern data platforms and enterprise data architectures using Databricks and relevant technologies. Ability to assess existing environments and develop target-state architectures using established architectural frameworks.
Data engineering proficiency: Strong knowledge of data movement, integration, transformation, cleansing, ETL processes, data warehousing, and data modeling, including entity-relationship, dimensional, and semantic modeling.
Databricks and Apache Spark technologies: Experience with several of the following technologies and familiarity with most: Databricks Lakehouse architecture, medallion design patterns, Unity Catalog, Apache Spark, PySpark, Spark SQL, Delta Lake, Auto Loader, Lakeflow Declarative Pipelines, workflow orchestration, Databricks Asset Bundles, Git integration, CI/CD, and Databricks SQL.
Cloud migration and platform optimization: Experience migrating data solutions from on-premises infrastructure, legacy systems, or other cloud platforms to Databricks. Ability to optimize queries, pipelines, data models, compute resources, and overall platform performance.
Governance, security, and operations: Understanding of data governance, lineage, access controls, data sharing, encryption, networking, platform administration, and cost management. Familiarity with DevOps or DataOps practices and deploying Databricks solutions across environments.
Programming and analytics: Expert-level proficiency in SQL and Spark technologies, including PySpark and Spark SQL. Familiarity with programming languages such as Python, C#, Java, Scala, R, DAX, MDX, or M is beneficial.
Emerging technologies: Experience with data science or machine learning is an advantage. Familiarity with Mosaic AI, MLflow, model serving, and generative AI capabilities is also desirable.
Consulting and client engagement: Ability to communicate complex technical concepts, data strategies, risks, and recommendations clearly to both technical and nontechnical stakeholders, including senior executives.
Leadership and people management: Demonstrated experience supervising teams, conducting performance appraisals, mentoring and coaching professionals, reviewing work, coordinating across teams, and motivating individuals toward shared objectives.
Business development: Ability to cultivate professional networks, establish relationships with senior executives, contribute to proposals, pursue new business opportunities, and develop strategies for acquiring new clients and expanding engagements.
Strategic thinking and problem-solving: Strong analytical, organizational, and decision-making skills, with the ability to interpret data, evaluate alternatives, and develop solutions aligned with business goals.
Collaboration and adaptability: A commitment to teamwork, inclusion, integrity, innovation, continuous learning, and delivering high-quality client outcomes in a dynamic consulting environment.
Benefits:
Competitive annual base salary: $159,000–$255,000 USD, depending on experience, skills, and geographic work location.
Annual incentive compensation: Target bonus opportunity of 14% for eligible employees, through additional cash and/or discretionary stock compensation opportunities.
Estimated total cash compensation: $181,260–$290,700 USD, combining the stated base salary range with the target bonus opportunity. Actual compensation may vary.
Healthcare coverage: Medical, dental, and vision insurance options.
Healthcare savings accounts: Access to Flexible Spending Accounts (FSA) and Health Savings Accounts (HSA), subject to plan eligibility.
Retirement savings: A company 401(k) savings and investment plan, with an employer match of 50% on the first 6% of employee contributions.
Paid time off: Choice Time Off (CTO) for vacation, personal needs, and sick time, with the allowance varying by years of service. New hires receive up to 20 days per calendar year.
Paid holidays: Recognition of up to 11 paid holidays each calendar year.
Family support: Adoption and fertility assistance, plus paid parental leave of up to 10 weeks.
Insurance and income protection: Life and accident insurance, along with short-term and long-term disability coverage.
Professional development: Opportunities to expand technical expertise, develop leadership capabilities, and work with emerging data technologies across diverse industries.
Career advancement: Exposure to strategic consulting engagements, senior client stakeholders, business development, and enterprise-level transformation initiatives.