Databricks Administrator

About the role

Develops, maintains, and enhances cloud-based data platform solutions and business applications with a focus on Databricks, Apache Spark, Delta Lake, and modern data engineering practices. Collaborates with data engineers, data scientists, analysts, business stakeholders, and technology teams to validate requirements, assess available technologies, and recommend scalable, secure, and cost-effective platform solutions.

Responsibilities

• Designs and supports Databricks workspaces, clusters, job workflows, data pipelines, governance controls, and automation capabilities to meet business and technical objectives.
• Builds, maintains, and optimizes scalable data pipelines using Apache Spark, PySpark or Scala Spark, Delta Lake, SQL, and medallion architecture patterns including Bronze, Silver, and Gold layers.
• Uses data engineering methodologies, programming languages, infrastructure tools, and solution design techniques to develop reliable, secure, and performant data platform solutions that meet business specifications.
• Implements and enforces data platform governance standards, including workspace administration, access controls, Unity Catalog, data lineage, security policies, and platform best practices.
• Validates functional requirements, builds technical specifications, and develops application, platform, architecture, and operational documentation.
• Performs analysis, design, development, testing, deployment, and support of data pipelines, platform workflows, and application components to solve business and technical requirements.
• Integrates new or enhanced Databricks platform capabilities, data processing components, orchestration tools, CI/CD pipelines, and cloud services into existing data environments.
• Optimizes Spark jobs, cluster configurations, storage patterns, and workflow designs for performance, reliability, scalability, and cost efficiency.
• Maintains platform health, troubleshoots production issues, supports incident resolution, and recommends corrective actions to improve platform stability and operational performance.
• Automates infrastructure provisioning and platform configuration using Terraform or similar infrastructure-as-code tools.
• Contributes to CI/CD processes for data workflows and platform deployments using tools such as GitHub Actions, Azure DevOps, Git, or similar development workflow technologies.
• Collaborates with data engineers, data scientists, analysts, architects, and business stakeholders to understand platform needs and deliver appropriate solutions.
• Supports change readiness initiatives, release planning, platform adoption, and communication of standards or best practices as needed.

Qualifications

• Applies advanced knowledge of data engineering, cloud platforms, Databricks administration, Spark-based processing, Delta Lake, and platform engineering practices.
• Serves as a subject matter resource for Databricks platform capabilities, standards, and best practices.
• Develops solutions to complex technical and business problems involving data pipelines, cloud infrastructure, platform governance, access management, workflow orchestration, performance optimization, and operational support.
• Works independently on assigned projects and platform initiatives, using judgment and discretion to evaluate alternatives, recommend solutions, and implement improvements.
• Collaborates across technical and business teams to define requirements, resolve issues, improve platform reliability, and support scalable data engineering practices.
• Provides technical guidance, coaching, or informal leadership to less experienced team members, especially in areas such as Databricks administration, Spark optimization, CI/CD, infrastructure-as-code, and data pipeline design.
• Contributes to standards, documentation, procedures, and best practices related to Databricks platform architecture, governance, development workflows, deployment patterns, and operational support.

Skills

• Advanced knowledge of data engineering, cloud platforms, Databricks administration, Spark-based processing, Delta Lake, and platform engineering practices.
• Experience with Databricks workspace administration, cluster management, job scheduling, Spark performance tuning, Delta Lake, SQL, data modeling concepts, and cloud-based data engineering practices.
• Hands-on experience with Databricks, Apache Spark, data pipelines, cloud platforms, SQL, version control, and collaborative development workflows.
• Experience with Unity Catalog, Databricks Asset Bundles, Apache Airflow or Databricks Workflows, MLflow, Great Expectations, dbt, Terraform, GitHub Actions, Azure DevOps, and other tools supporting modern data platform development and operations.

Benefits

Generous Paid Time Off
401K and Pension Plan
Paid Holidays
Family Support (Paid Leave, Surrogacy, Adoption)
Medical, Dental, Vision, and Life Insurance
Long-term and Short-term Disability Insurance
Health Savings Account / Flexible Spending Account
Education Assistance
Employee Development Resources
Employee Wellness, Leadership Development and Mentorship Programs

Pay

TBD

Schedule

TBD