.png)
CSQ227R215
As a Staff Designated Engineer and tech subject matter expert, you will partner closely with our Field and Engineering teams to deliver high-touch specialised support and tailored technical solutions for Databricks' largest and most strategic customers in the Digital Native Business (DNB) segment. In this customer-facing role, you will leverage your technical expertise in Apache Spark™ and other data technologies to triage and resolve complex product issues and unblock our customers’ most critical technical challenges.
The Impact You Will Have:- Perform advanced Troubleshooting and Root Cause Analysis to resolve performance and reliability issues in Spark, SQL, Delta, Streaming, and Databricks runtime features using tools like Spark UI metrics, Mosaic AI Model Service, DAGs, and event logs.
- Discover requirements for continuous monitoring to detect early performance issues, working with R&D and NOC teams to optimise the DNB customer environments.
- Build Rapid POCs, Test/Deploy/Monitor the solutions built by Databricks Engineering to address customer challenges and showcase advanced Spark/ML/AI runtime capabilities aligned with their business goals.
- Develop comprehensive playbooks and maintain a knowledge base of common issues and solutions for Spark, ML, and AI workflows.
- Train customer engineering and business teams on best practices in performance tuning, debugging, and effectively leveraging Databricks Features.
- Pilot new best practices processes/ programs, champion process improvements, and collaborate with cross-functional teams to enhance the customer experience.
- Advocate for customers in business review meetings and maintain close relationships as a trusted advisor and primary technical point of contact.
- Collaborate onsite with Field Engineering, Sales, and Product teams during customer engagements and technical presentations to provide rapid solutions to production-impacting issues, demonstrating deep technical expertise and building strong customer trust.
- Technical Expertise in Big Data and Spark: 10+ years of experience designing, building, and troubleshooting distributed computing applications, with 4+ years delivering production-scale Spark/ML/AI solutions using Python, Java, or Scala.
- Data Engineering Specialisation: Hands-on expertise with Data Lakes, SQL-based databases, and Cloud-based Data Warehousing/ETL tools like Snowflake, Redshift, Bigquery, etc
- Advanced Tech Skills: Deep knowledge of Spark core internals, Delta/Iceberg, JVM optimisation, and memory management, with additional proficiency in AI ecosystems like Machine Learning, Deep Learning, and Generative AI.
- Cloud and CI/CD Skills: Practical experience with AWS, Azure, or GCP, coupled with expertise in building and managing CI/CD pipelines, monitoring, and alerting systems.
- Customer-Facing Experience: 3–5 years in customer-facing roles such as Technical Account Manager or Solutions Architect, demonstrating strong communication, relationship-building, and problem-solving skills.
- Advanced Proactive Problem Solving Skills: Proven ability to anticipate, identify, and mitigate risks while planning solutions for production challenges. Effectively use sound business judgment, risk avoidance and subject matter expert resources to coordinate team efforts to solve problems.
- Collaboration and Leadership: Proven ability to work with cross-functional teams and senior leadership to address roadblocks, mitigate risks, and drive customer success while creating impactful documentation for self-service solutions.
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Skills Required
- 10+ years designing, building, and troubleshooting distributed computing applications
- 4+ years delivering production-scale Spark, machine learning, or artificial intelligence solutions
- Production experience with Python, Java, or Scala
- Hands-on expertise with data lakes, SQL databases, and cloud data warehousing or ETL tools such as Snowflake, Redshift, or BigQuery
- Deep knowledge of Spark internals, Delta or Iceberg, JVM optimization, and memory management
- Proficiency with machine learning, deep learning, and generative AI ecosystems
- Experience with AWS, Azure, or Google Cloud Platform
- Experience building and managing CI/CD pipelines, monitoring, and alerting systems
- 3–5 years of customer-facing experience in roles such as Technical Account Manager or Solutions Architect
- Strong communication, relationship-building, problem-solving, collaboration, and leadership skills
- Ability to anticipate and mitigate production risks and coordinate cross-functional solutions
- Ability to create impactful technical documentation and self-service solutions
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
-
Healthcare Strength — Company materials highlight comprehensive medical, dental, and vision coverage alongside mental-health resources, wellness reimbursements, and business travel insurance. Offerings are described as broad and modern, with core health coverage consistently emphasized.
-
Parental & Family Support — Paid parental leave is explicitly called out, with details such as up to 20 weeks for birthing parents and up to 12 weeks for non-birthing parents in the U.S. Public materials also reference family-forming support, reinforcing the focus on families.
-
Wellbeing & Lifestyle Benefits — Wellness programs and perks include gym reimbursement, periodic wellness events (e.g., yoga, massages), and in-office meals and snacks in many locations. Personal development funds and discounts further enhance lifestyle and growth support.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
