Head of Data Engineering

About Databook

Databook is the world’s first AI-powered enterprise customer intelligence platform. The company’s award-winning SRM platform leverages advanced AI and NLP to empower the world’s largest B2B sales teams to create, manage, and maintain strategic relationships at scale. The platform ingests and interprets billions of financial and market data signals to generate actionable sales strategies that connect the seller’s solutions to a buyer’s financial pain and urgency. On average, Databook clients achieve 5x more customer meetings, 3x more pipeline, 2.5x larger deals and 1.5x faster cycle time. Dubbed “Moneyball for Sales”, Databook was founded in 2017 to give enterprise sales representatives and go-to-market teams a differentiating advantage. Today, leading enterprise companies rely on Databook to help their teams engage as experts – improving the buying experience for customers and accelerating revenue acquisition. Our customers include AWS, Qualtrics, Microsoft, Salesforce, SAP, Databricks, Splunk and more. We are a Series B company backed by Bessemer Ventures, DFJ Growth, M12 - Microsoft’s Venture fund, Salesforce Ventures and Threshold Ventures. We have a friendly, entrepreneurial and collaborative culture. We are headquartered in Palo Alto, CA with a distributed team working across the globe.

 

Opportunity

As the Head of Data Engineering, you will play a pivotal role by driving the vision and execution of our data capabilities. You have a successful track record demonstrating the business value of data engineering projects by tying them to new customer-facing products. You will work closely with Data Scientists, Product Managers, ML Engineers and Software Engineers by building the data architecture that informs decisions and drives our customer-facing capabilities. The ideal candidate has strong data infrastructure and data architecture skills, a proven track record attracting and developing a diverse team of data engineers, strong operational skills to drive efficiency and speed, solid project management skills and a vision for how data engineering can drive product. As the most-senior engineering lead in our India office, you will have experience collaborating with leadership across both technical and business topics and a track record enhancing culture in your working environment.

 

Responsibilities include

• Drive technical and process innovation to increase the maturity and capability of Infrastructure data engineering team and practices.
• Establish the processes needed to achieve operational excellence in data fidelity, data privacy, system reliability, and enabling rapid experimentation and data-informed decisions.
• Drive the design, building, and launching of new data models and data pipelines in production.
• Define and manage SLAs for all data sets and processes running in production.
• Drive data quality across the product vertical and related business areas.
• Strong familiarity with cloud platforms like AWS and working knowledge of the Databricks product suite.
• Drive the design, building, and launching of new data models and data pipelines in production.
• Attract, mentor and develop a high performing data engineering team.

 

About You

• 12+ years of relevant experience in Analytics, BI and Data Warehousing.
• BS/MS in Computer Science, Math, Physics or other technical discipline.
• Proven experience building, scaling and leading high-performing teams, with the ability to motivate, mentor, and inspire and in managing managers. 
• Ability to develop a clear data strategy, aligning data initiatives with business objectives.
• Experience scaling and managing a growing team, and in managing managers.
• Experience leading in a highly cross-functional environment, collaborating closely with Engineering, Product Management and Data Science.
• Communication and leadership experience initiating and driving company-wide strategic initiatives.
• Proven hands-on experience in architecting and building scalable data systems, including ETL processes, distributed systems for data processing, data migration and quality/observability.
• Experience in SQL with advanced query optimization techniques and Python.
• Solid understanding of how experimentation (A/B testing) works.
• Experience in AI and ML lifecycle is a plus. 
• A passion for staying updated on the latest advancements in data including ML and AI and a strong drive to innovate and deliver high-quality solutions.

Ideal candidates will also have

• High level of self motivation with great organizational skills.
• Experience reviewing and providing fee