Why this job is exciting

Sourcegraph’s Data & Analytics team empowers every part of the business with the data infrastructure and insights they need to make better decisions. 

As our first Data Engineer Lead, you will play a critical part in building a scalable data platform that will enable our rapid growth. You will help design and implement the data infrastructure and pipelines that will reliably consume and analyze large volumes of complex data from different sources, and that will scale with the company and its growing data needs. You and your team will own all things data, including our cloud data pipelines, our internal tracking code, and our data models and metrics. As an early member of the team, you will influence how the Data team works and how we support the company, across Product, Sales, Marketing, Engineering, Operations, and more, in making better decisions. 

Within one month you will:

• Complete your new hire onboarding checklist
• Become more familiar with our product and value propositions by completing demos and other training sessions
• Meet with all members of the Data & Analytics team, and with stakeholders across the business in Finance, Strategy, Sales Operations, Marketing Operations, Product, and more
• Onboard onto our data infrastructure and BI tools (BigQuery, Looker, Amplitude), and get familiar with our architecture, data sources, and pipelines
• Assess and document areas for improvement and optimization in the current data ecosystem

Within three months you will:

• Understand and document the entire data architecture and ecosystem
• Define a short and long-term strategy to modernize and scale data capabilities as the company grows
• Mentor team members on data best practices and principles
• Work closely with stakeholders to gather requirements and contribute to the Data & Analytics team roadmap 
• Drive improvements in our data discoverability through documentation and thoughtful modeling of our data
• Evaluate and potentially implement new systems and tools (such as Dbt, Airflow, Snowflake, Redshift, Storm, Spark, and more)

Within six months you will:

• Become the owner of our data architecture, data sources, and technologies
• Analyze all of our data sources and develop or improve our mappings, transformation rules, aggregations and ETL specifications
• Define our data quality standards, and implement the processes, testing, and monitoring needed to achieve high data quality
• Build a data access layer to provide data services to stakeholders
• Own and execute portions of the Data & Analytics roadmap and OKRs

About you 

You are strongly aligned with our values and inspired by our mission to make it so that everyone can code.

Qualifications:

• Demonstrated background (6+ years) in data engineering or analytics engineering roles
• Professional experience working with data pipelines, ETL or ELT tools, data warehouses, and business intelligence tools
• Proficient in writing analytic SQL
• Proficient with the command line, git, and at least one scripting language
• Comfortable building data pipelines using a wide variety of data sources, such as frontend tracking libraries like Snowplow, PostgreSQL, Google Analytics and Google Tag Manager, HubSpot or similar, Salesforce, Zendesk or similar, and implementing custom code to transform data
• Independent and high-agency, with the ability to prioritize and execute multiple tasks simultaneously
• Excellent verbal and written communication skills, including an ability to communicate with both business and technical teams

Nice to haves:

• Software engineering experience, particularly in implementing and maintaining tracking (event logging) code
• Experience in TypeScript and Go
• Experience with cloud infrastructure/platforms (AWS, Azure, Google Cloud Platform)

Interview process [~5.5 hour total interview] 

Click here to read more information in our Handbook about the types of interviews we use at Sourcegraph.

• You apply.
• [30 min] Recruiter screen with Kelsey Nagel
• [30 min] Hiring Manager screen with Lauren Anderson
• [1 hr] Resume deep dive (aka Topgrade) with Lauren Anderson
• [1 hr] Take-home Assignment
• In-depth Interview stage:
  • [45 min] Assignment review/working session with Eric Brody-Moore & Engineering team member
  • [45 min] Cross-functional interview with Kelsey Brown & PM team member 
  • [30 min] Values interview 
  • [30 min] Department head interview with Dan Adler
• Any other informal conversations with people who you would be working closely with but didn’t get to meet during the interview process.
• We check references & make you an offer

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