Junior Data Engineer (New York, NY)

B LabNew York, NY
$62,900 - $83,000Remote

About The Position

As a Junior Data Engineer within the Data & ML Platforms pillar, you build and maintain the data pipelines and infrastructure the rest of the Data & AI team depends on. Your first priority is unblocking the onboarding of new data sources — currently one of the team's top hiring priorities, paused pending this hire. You will absorb data engineering work currently split between the Senior Machine Learning Engineer and the Pillar Lead, freeing them to focus on ML infrastructure and platform strategy respectively. You will work closely with the Senior Analytics Engineer on core data modeling and with the Data Governance Lead on data standards, definitions, and compliance.

Requirements

  • A BA/BS in Computer Science, Information Technology, or a related field strongly preferred
  • Minimum of 2+ years of experience in data engineering
  • Experience working in a DevOps-oriented culture that prioritizes continuous integration and continuous deployment
  • Proficiency with Git and collaborative version control workflows (e.g., branching, pull requests, code review)
  • Experience with Infrastructure as Code (e.g., Terraform, CloudFormation, or CDK) for provisioning and managing cloud infrastructure
  • Proven experience in designing and deploying data solutions
  • Experience designing, building, and onboarding new data sources into ETL/ELT pipelines
  • Ability and desire to take product/project ownership
  • Proficiency in SQL and experience with scripting languages such as Python, Java, or Scala
  • Experience with data pipeline and workflow management tools
  • Excellent communication skills

Nice To Haves

  • Strong knowledge of big data tools and frameworks such as Hadoop, Spark, or Hive is a plus
  • Experience using AI coding assistants and other AI tools to improve development speed and productivity

Responsibilities

  • Own Pipeline Development End-to-End: Design, build, and maintain robust, scalable ETL/ELT pipelines that reliably deliver clean data to the platform.
  • Add New Data Sources: Evaluate, scope, and integrate new data sources as they're identified.
  • Partner Across Pillars: Work continuously with Network Priorities, Regional Enablement and AI Enablement to understand incoming data needs and translate them into pipeline work.
  • Monitor & Troubleshoot: Proactively identify and resolve pipeline failures and data quality issues before they affect downstream users.
  • Support Foundational Data Models: Work with the Senior Analytics Engineer to maintain the core data models the rest of the team depends on.
  • Ensure Data Availability for Consumers: Make sure the data needed by Data Analysts and the Senior Machine Learning Engineer is reliably available.
  • Follow Data Governance Standards: Apply the data standards, definitions, and sensitivity classifications set by the Data Governance Lead.
  • Evaluate Pipeline Tooling: Explore and pilot new ETL/ELT tools or approaches that could improve onboarding speed or pipeline reliability.
  • Quantify Impact: Track and articulate how pipeline reliability and onboarding speed affect downstream analytics and ML work.

Benefits

  • An annual salary in the range of $62,900 - $83,000 based on experience and skills
  • Excellent health benefits package including access to medical, vision and dental coverage
  • Paid time off for vacation - in your first year, you’ll start with 15 days (prorated in a to your start date)
  • Additional paid time off for organizational closures
  • 403(b) with a match of up to 3%
  • Unlimited sick and personal time - if you need it, use it
  • After your first year of employment, 40 hours paid time off for community service; paid parental leave; and time and budget for your professional development (we assess this PD budget annually)
  • A remote-first workplace
  • A flexible work environment with the ability to plan your work week around your personal commitments
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