Lead Data Engineer
Here at Hinge we embrace a data-centric, facts not ‘feel’ culture and are looking for a sharp Lead Data Engineer who will be responsible for the management, design, architecture, and development of our core data platform, which is a vital part of decision-making at Hinge. As Lead Data engineer you’ll be an integral member of our engineering team and report directly to the Head of Engineering.
Roles / Responsibilities
- Formulate best practices for the data team codebase
- Set quarterly and annual priorities for the Data Engineering team
- Coach, lead, and motivate Data Engineering team members to deliver on time and according to spec
- Hire for data engineers when necessary
- Help analyze performance throughout the stack to optimize data pipelines and workflows
- Work with Lifecycle, Marketing, Customer Service, and other Hinge teams to understand their needs and continually optimize BI stack at the data warehouse level to accommodate those needs
- Write high-quality code that is self-explanatory, tested, and meets objectives as described in functional specifications
- Collaborate with other data, machine learning, backend, and client (iOS and Android) engineers and participate in data team code reviews
- Drive projects to completion while providing guidance to team members
- Over 5 years of engineering experience in a fast-paced environment, including at least 3 years experience in scalable data architecture, fault-tolerant ETL, and monitoring data quality in the cloud
- At least 1 year of experience leading data engineering teams
- Experience in setting up, maintaining, and optimizing data infrastructure (preferably on AWS)
- Willing to roll up your sleeves and hit the ground running with a commit on day one. You will be spending 70% of your time developing and 30% of the time managing
- Ability to lead by example and clearly communicate opinions on best practices
- You know how to ask the right questions, evaluate tradeoffs fairly and holistically, and apply analytic reasoning skills to get the right answer most of the time
- You are deeply curious and driven to understand our business, product, and technology, and you apply that knowledge to create better data capabilities
- You are exceptional at building a data engineering team and painting a compelling vision for the team
- Always excited to share ideas
- You communicate clearly and have the ability to own complex projects end-to-end while coordinating with other, non-engineering teams as necessary
- Required skills:
- Fluency in SQL (we use Postgres and Redshift)
- Fluency in Golang and/or Python
- Streaming, processing, and queueing with NSQ, Celery, Kafka, Kinesis (or similar)
- Preferred skills and tools:
- Data integration tools such as Segment and mParticle
- Analytics tools such as Mixpanel and Looker
- Data pipelining tools such as Airflow and Luigi
- NoSQL databases/datastores such as MongoDB, Redis, and DynamoDB
- Big data tools such as Hadoop and Spark
Objectives in the first three months
- Learn our systems and take ownership thereof to improve the design and implementation of our scalable ETL processes and data pipelines
- Develop Data Engineering team hiring strategy
- Establish Data Engineering team policies
- Partner with Product, Marketing, and Data Science to deliver a Data Engineering roadmap that supports business objectives
- Review each data team Pull Request (GitHub)
- Plan and help estimate team’s work in weekly Sprint Planning meetings
We believe the quality of your relationships determines the quality of your life. So when it comes to your most important relationship, it makes sense to take a more thoughtful approach. Hinge provides an alternative to swipe culture by creating smart matches and natural conversations among people who are on the same page. That’s why 75% of our first dates turn into second dates, and why we’re the #1 mobile-first dating app mentioned in the NYTimes Wedding section. Hinge is where the next generation is going when they’re over dating games and ready to find meaningful connections.
Our cultural attributes:
- Open: Invite and deeply consider challenges and criticism.
- Candid: Share your genuine thoughts and opinions directly, in real time.
- Kind: Be empathetic, communitarian and trustworthy.
- Bold: Proactively identify and pursue opportunity. Think big and don’t be afraid to take calculated risks.
- Discerning: Think and act using the appropriate combination of principles, common sense, data and insight.