Back River Search Group

Sr. Manager, Data Engineering

Back River Search - San Francisco, CA

Overview

Our client is dedicated to helping our members lead healthy financial lives. That’s why we offer an award-winning bank account that doesn’t charge unnecessary fees, gives members early access to their paychecks, and helps them save money automatically. Hundreds of thousands of people use their mobile app and debit card to make purchases, track spending, save for the future, and more.

They believe the big banks fail to help their members achieve financial health - and in many cases work against it, charging hundreds of dollars in hidden fees and pushing products that drive people into debt. They don’t think it needs to be this way, so we’re out to beat them.

They have one of the most experienced management teams in Fintech and just raised a $70M Series C funding round, led by Menlo Ventures, to fuel their growth. If you’re looking to join a small but fast-growing company with a beloved, daily-use product and an authentic mission that puts people first, we want to meet you.

Our client is a technology and data-driven consumer bank. We are amassing vast amounts of data that we want to use to ensure the best practices in risk management, new user acceptance, information security, underwriting, and more. Our ML and Data Science team occupies a critical role in the company, creating models and infrastructure that allow us to evaluate events in realtime in new, efficient, and accurate ways so as to minimize fraud and scale our ability to manage risk.

What You’ll Do

In this role, you’ll be responsible for managing the team overseeing the design, development and operations of large-scale, real-time data systems. The ideal candidate will be excited by the prospect of owning, optimizing or even re-designing our company’s data architecture and building out a team to support our next generation of products and data initiatives. Your Data Engineering team will support our software developers, database architects, data analysts, data scientists, and machine learning engineers on back-end data initiatives. We’re looking for a leader who is self-directed and comfortable supporting the data needs of multiple teams, systems and products.

Your responsibilities will include:

  • Hire world class talent and provide technical guidance, career
  • development, and mentoring to team members
  • Build the infrastructure required for optimal extraction,
  • transformation, and loading of data from a wide variety of data
  • sources using SQL and AWS ‘big data’ technologies
  • Work with stakeholders including the Analytics, Risk, Machine
  • Learning, and Technical Operations teams to assist with
  • data-related technical issues and support their data infrastructure
  • needs
  • Participate in key technical and design discussions with technical
  • leads in the team as a hands-on manager
  • Act as a project manager for the projects that your team is
  • responsible for
  • Provide technical leadership to your team by giving guidance on
  • designs and coding when time allows
  • Help manage and consult in designing our data governance
  • initiatives

Qualifications & Requirements:

  • 3+ years of experience leading data engineering teams
  • 5 years of experience in designing, implementing, optimizing and
  • operationalizing real-time big data analytics systems including
  • data-pipelines, data warehouses and enterprise wide
  • data-flows
  • Passion and drive to change consumer banking for the
  • better
  • You've earned a bachelor’s degree in Computer Science or other
  • technical field
  • Expertise with leading, mentoring, training, and/or hiring a team
  • of talented engineers
  • Understanding of the tradeoffs between different big data
  • solutions
  • Excellent verbal and written skills
  • Strong analytic skills related to working with unstructured
  • datasets.
  • Experience with a variety of traditional, streaming, and big data
  • tools such as:
    • Hadoop ecosystem: Hadoop, Hive, Spark
    • Kafka, Sqoop, Flume
    • Cassandra, Mongodb
    • Airflow or other workflow scheduler
    • Data Warehouses: Redshift, Snowflake
    • SQL databases, including MySQL, Postgres
    • AWS cloud services: EC2, EMR, RDS
    • Stream-processing systems: Storm or Spark-Streaming,
    • etc.
    • Advanced SQL, Python, Java and/or Scala


Posted On: Wednesday, February 6, 2019



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