Staff Data Engineer

Position Summary...

What you'll do...

Bonobos is looking for a Staff Data Engineer who is hungry to make the company more empirical and customer-centric as a member of the Data Engineering and Governance team.

At Bonobos, we’re redefining how customers browse, discover and shop for apparel. As the first digitally native apparel company in the US, we are poised to make groundbreaking advances in how customers shop. Bonobos is uniquely positioned to delight customers by connecting our showroom stores (we call them Guideshops) to our online experiences. We're inventing the future of retail. Our customers are fanatical about our clothes and our world-class customer service.

As a Staff Data Engineer, you can look forward to rolling up your sleeves and digging into our data to help develop and maintain our core data platforms and tools that everyone can rely on. This includes creating and validating the data engineering patterns we use. This role will be responsible for not only individual contribution of the data ecosystem core platforms but the data engineering quality and patterns it uses. The data core platforms are responsible for the ingress / egress of data into the ecosystem as well as an orchestration layer of complex data transformations, refining raw data from source into a rationalized view of enterprise data that can be consumed in a governed way. This system is also responsible for the delivery of data to other systems that rely on the rationalized view of enterprise data. Other engineering platform opportunities may include building out a data registry and customer repository. You will be partnering with Analysts, Engineers, Data Scientists and Business Stakeholders to build out capabilities that make an impact across the entire Organization.

Sample Tech From Our Stacks:

• Snowflake Data warehouse

• Kafka based streaming platform

• DBT

• Custom pythonic application abstractions to manage PUB/SUB to kafka

• Custom customer informatics services

• Custom data registry services

• Common Components: Snowflake, Flask, AWS: RDS Postgres, Redis Queue, Redis Graph, Redis Key Value Store, AWS: S3, AWS: ECS/ECR, AWS: Lambda / Gateway, and AWS: Sagemaker

• DevOps Tools: Github, Circle CI, Terraform, Ansible, Containers, and Serverless

• Methodologies: Agile, Infrastructure as Code, Microservices, and Cleancode

What you'll do...

• Analyzes, designs, codes, tests, configures and modifies software for the functional delivery of data platforms, pipelines and solutions using various programming languages, technologies and development methodologies.

• Designs, develops, tests, debugs and implements data platforms, pipelines, solutions and/or software tools, and utilities for the purpose of assuring acceptable performance and service levels.

• Owns the automated delivery of data platforms, pipelines and solutions using source control, infrastructure as code, continuous integration throughout the entire delivery model

• Ensures that implemented data platforms, pipelines and solutions are successfully monitored, with relevant alerts, logging and tracing that guarantee the relevant durability, availability and performance.

• Ensures the data is modeled correctly for consumption

• Validates that data platforms, pipelines and solutions follow data governance policies, standards and intent

• Completes technical documentation that adds value, including but not limited to testing, training governance and software delivery

You…

• Have 7+ years of experience in a Data Engineering or similar role

• Proficiency Python and other programming languages

• Enjoy working on a Scrum Team in an agile delivery environment

• Ability to mentor engineers and drive engineering excellence

• Self-directed with Implementing, designing, guiding and mentoring Deployment & Delivery

• Self-directed with gathering and assimilating Development Requirements

• Can lead and validate engineering design sessions

• Can lead and validate data modeling

• Self-directed on simple to complex Debugging / Troubleshooting problems

• Can lead and validate the implementation, design, and mentoring a team through M.A.L.T. engineering practices

We...

• Work hard because we love what we’re doing, but also believe in balance (say hello to unlimited vacation days!)

• Back up our talk with a competitive compensation and benefits package, challenging projects, random acts of team-wide fun and awesome co-workers that feel like family

• Value self-awareness, intellectual honesty, judgment, empathy & positive energy – often over experience

• Are located in the Flatiron District in the heart of Manhattan

• Have a passion for delivering a superior experience to our customers, clients, vendors & one another

• Are excited to hear from you!

Minimum Qualifications...

Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.

Option 1: Bachelor’s degree in Computer Science and 4 years' experience in software engineering or related field. Option 2: 6 years’ experience in software engineering or related field. Option 3: Master's degree in Computer Science and 2 years' experience in software engineering or related field.
3 years' experience in data engineering, database engineering, business intelligence, or business analytics.

Preferred Qualifications...

Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.

Data engineering, database engineering, business intelligence, or business analytics, ETL tools and working with large data sets in the cloud, Master’s degree in Computer Science or related field and 4 years' experience in software engineering or related field