Technical Lead - Databricks Developer
Description
We are partnering with a world-class healthcare and biotechnology leader to find a highly skilled Technical Lead - Databricks Developer. In this critical role, you will design and implement robust, scalable data engineering solutions using the Databricks Lakehouse architecture.
This position is ideal for a hands-on technical leader who excels at bridging the gap between complex data processing and client business needs. You will collaborate closely with enterprise architects and lead engineers, taking ownership of end-to-end data pipelines, optimizing system performance, and driving modern data governance practices in a dynamic corporate environment.
Key Responsibilities
- Architecture & Solution Design: Collaborate with architects and lead engineers to design and build solutions that meet both functional and non-functional enterprise requirements.
- Pipeline Engineering: Architect, build, and manage complex, scalable data pipelines supporting both batch and streaming data processing.
- Databricks Orchestration & Governance: Implement and manage Databricks workflows orchestration, leveraging Unity Catalog for data governance and access control.
- Performance Optimization: Proactively identify bottlenecks and drive rigorous performance optimization initiatives to maximize efficiency and significantly reduce compute costs.
- Client Engagement: Work directly with customers and stakeholders, utilizing exceptional communication skills to translate business challenges into technical deliverables.
Required Qualifications
- Databricks Expertise: Must have successfully implemented at least one enterprise project end-to-end within Databricks. Deep understanding of the Databricks Lakehouse concept and its implementation in large-scale environments is mandatory.
- Core Data Components: Proven, hands-on experience with core ecosystem components including Delta Lake, Unity Catalog, Databricks Workflows, and basic data governance principles.
- Programming & Frameworks: Excellent, production-level coding skills in Python, strong proficiency in SQL and Spark-SQL, and extensive knowledge of Apache Spark and Hive data processing frameworks.
- Technical Foundations: Strong foundational knowledge of data structures, algorithms, and advanced analytical problem-solving skills.
- Communication Skills: Exceptional verbal and written communication skills with the proven ability to engage confidently and directly with enterprise clients.
Preferred Qualifications
- Industry Trends: Demonstrated knowledge of relevant industry standards, emerging data engineering trends, and modern cloud ecosystems.
- Continuous Growth: A strong, proactive attitude toward learning new skills, upskilling in cutting-edge data technologies, and mentoring peers.
Education
- Bachelors or Masters in Information Technology, Computer Science or relevant field.
Work Environment
This job operates in a professional office environment. This role routinely uses standard office equipment, including but not limited to, computers, phones, and photocopiers.
Physical Demands
This position requires the frequent and repetitive use of a computer, keyboard, and mouse. Hand and finger dexterity is required.
Other Duties
Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.
EEO
Saama provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.