Databricks Solutions Architect Senior Manager
J
JobgetherData consulting
Based in the United StatesFull-TimeManager
SalaryCompetitive 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.
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Job Details
- Experience
- At least 7 years of experience in professional services, technology consulting, data engineering, or a related industry.
- Required Skills
- SQLETLSparkCI/CDDatabricksPySpark
Requirements
- Bachelor's degree in Management Information Systems, Computer Information Systems, Analytics, or another relevant discipline.
- At least 7 years of experience in professional services, technology consulting, data engineering, or a related industry.
- Databricks Certified Data Engineer Professional or Databricks Certified Machine Learning Professional certification.
- Experience designing modern data platforms and enterprise data architectures using Databricks and relevant technologies.
- Knowledge of data movement, integration, transformation, cleansing, ETL, data warehousing, and entity-relationship, dimensional, and semantic modeling.
- Experience with several, and familiarity with most, of Databricks Lakehouse, medallion 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.
- 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 platform performance.
- Understanding of data governance, lineage, access controls, data sharing, encryption, networking, platform administration, and cost management.
- Expert-level proficiency in SQL and Spark technologies, including PySpark and Spark SQL.
- Required professional certification as a Databricks Certified Data Engineer Professional or Databricks Certified Machine Learning Professional.
- Experience supervising teams, conducting performance appraisals, mentoring and coaching professionals, and reviewing work.
- Ability to communicate technical concepts, strategies, risks, and recommendations to technical and nontechnical stakeholders, including senior executives.
- Ability to contribute to proposals, cultivate professional networks, pursue business opportunities, and develop client relationships.
Responsibilities
- Lead the design of modern data platforms using Databricks, Lakehouse architecture, medallion design patterns, and cloud technologies.
- Assess client data environments and develop data strategies and roadmaps aligned with organizational priorities.
- Lead the design, development, migration, and optimization of data pipelines, ETL processes, warehouses, databases, and platforms.
- Guide adoption of Databricks capabilities, including Apache Spark, PySpark, Spark SQL, Delta Lake, and workflow orchestration.
- Establish data governance frameworks and use Unity Catalog to manage data assets, lineage, permissions, and sharing.
- Optimize pipelines, queries, models, compute resources, and platform configurations; oversee deployment, monitoring, and cost optimization.
- Manage engagement teams, project plans, deliverables, quality reviews, risks, and client stakeholder communications.
- Advise clients on business needs and communicate recommendations through data storytelling, presentations, and strategic guidance.
- Supervise, coach, mentor, and evaluate team members and support their professional development.
- Contribute to proposals, pursuit activities, client relationships, and opportunities to expand engagements.
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