Data Engineering Lead
Location: Connecticut, Colorado, New Jersey, New York - hybrid
Data Engineering Lead
As a Data Engineering Lead, you will lead a team of engineers to build innovative solutions that empower entrepreneurs worldwide. In this role, you and your team will build backend streaming data pipelines, integrations with third party SaaS applications, complex analytics features and work closely with application engineering teams. You will take an active role in architecture and solution design and help optimize solution performance and reliability. As a result you will help Techstars entrepreneurs and investors.
We believe in sustainable software development using Agile Development methodologies and mature devops practices to quickly and consistently provide value. We believe in creating robust, performant, maintainable, observable solutions. As an organization we value innovation and collaboration.
About the role:
- Design, build and deploy quality data pipelines, models, integrations and APIs in an agile team environment.
- Lead a team to deliver solutions that allow for 10x growth of techstars pipeline of startups and our accelerator programs
- Mentor team members on standards, best practices and implementation of technology.
- Work with Engineering Leadership on design and implementation of technical systems.
- Support Product Owner with OKRs, Sprint planning and stakeholder meetings as a technical resource.
- Maintain uptime and SLA of deployed software systems.
- Foster technical growth within your team by encouraging collaboration and innovation.
- A team mentality towards accomplishing projects
- Ability to breakdown, prioritize and sequence development tasks for other engineers for high team utilization
- Desire to mentor and grow engineers on the team
- Knowledge of methodologies for testing quality, release management, incident response and issue resolution
- Experience developing robust APIs
- Diverse experience with languages (ie. SQL, Python, Node, Scala)
- Ability to create risk mitigation strategies for system upgrades and code releases
- Ability to analyze appropriate technology stacks and major infrastructural components.
- Strong DevOps skills
- Track record of building reusable and cohesive architecture across applications
- Experience creating technical designs that fulfill product requirements
- Coding standards utilization (Unit tests, formats, use of libraries, well structured, reusable, high quality)
- 5+ years creating secure, reliable and performant enterprise level data cleansing, statistical modeling and analytics solutions (prefer fintech experience).
- 5+ years working on a data platform using open source technology (Kafka, K8s, Redis) and cloud infrastructure or operating as managed services.
- 5+ years experience with relational and non-relational database architecture (postgres a plus)
- 3+ years leading a team and mentoring other engineers
Compensation: $135,000 - $155,000 with 10% bonus.
The Techstars worldwide network helps entrepreneurs succeed. Founded in 2006, Techstars began with three simple ideas—entrepreneurs create a better future for everyone, collaboration drives innovation, and great ideas can come from anywhere. Now we are on a mission to enable every person on the planet to contribute to, and benefit from, the success of entrepreneurs. In addition to operating accelerator programs and venture capital funds, we do this by connecting startups, investors, corporations, and cities to help build thriving startup communities. Techstars has invested in more than 3,000 companies that today have a combined market cap valuation of $96.6 Billion. www.techstars.com
Techstars is an affirmative action, equal opportunity employer and does not discriminate on the basis of race, sex, age, national origin, religion, physical or mental handicaps or disabilities, marital status, Veteran status, sexual orientation, gender identity nor any other basis prohibited by law.
Techstars uses E-Verify to check the work authorization of all new hires. For more information about E-Verify, please see the following:
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