Senior Engineering Manager - Enzyme

Навыки

• Data Lake
• Распределённые системы
• ETL / ELT
• Spark

О компании и продукте

• 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 .
• At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. We are the Lakeflow Engineering team, responsible for Databricks ETL product line such as Spark Declarative Pipelines, Structured Streaming, and Ingestion. We run one of the world's biggest (if not the biggest) data engineering platforms - responsible for processing exabytes of data daily for tens of thousands of customers. We're seeking a dedicated Engineering Leader to spearhead the Materialized Views engineering team
• The team is responsible for building next generation Materialized View features for both ETL workloads and for query acceleration. The main responsibilities include

Задачи

• You will lead an engineering team building the next-generation Materialized View features for the Databricks Lakeflow platform
• You will oversee sustained recruitment of top-tier talent, and upskilling talent on the team
• You will build processes to implement product vision and strategy, according to organizational goals and priorities
• You will build software that is not just high quality but easy to operate

Требования

• Minimum 3 years of experience in managing top-tier engineering teams
• 5+ years experience building data infrastructure systems such as Apache Spark™ or database internals
• A passion for database systems, storage systems, distributed systems, or performance optimization
• Experience working with product management, and directly with customers
• ability to understand customer needs
• Can ensure the team builds high quality and reliable infrastructure services
• Experience being responsible for testing, quality, and Service Level Agreements of a product
• Experience building and managing teams in a complex technical domain, such as on distributed data systems or database internals
• Expertise in attracting, hiring and coaching engineers, who will meet the Databricks hiring standards
• Experience up-leveling teams via hiring top-notch talent and growing existing team members

Условия

• At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees

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