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Scratch Financial logo
Scratch Financial

Scratch Financial is the world's simplest patient financing solution.

Senior Data Engineer, Engineering & Operations

Data EngineerData EngineerOtherRemoteSeniorTeam 11-50Since 1912H1B SponsorCompany SiteLinkedIn

Location

New York

Posted

152 days ago

Salary

$140K - $180K / year

Seniority

Senior

Bachelor Degree5 yrs expEnglishAirflowPySparkPythonSQL

Job Description

Senior Data Engineer, Engineering & Operations

Scratch Financial

• Define partner onboarding and clean room architecture patterns across Snowflake, LiveRamp, and Databricks that are secure, scalable, and repeatable • Configure and manage partner-specific clean room environments; deploy and manage Python-based libraries within the platform ecosystem • Establish and maintain MLOps practices, including model serving, monitoring, and pipeline orchestration for AI/ML features deployed within the platform ecosystem • Own design and enforcement of granular RBAC policies and least-privilege service accounts • Serve as the technical lead for onboarding new partners, implementing privacy-preserving controls (e.g., aggregation thresholds and anonymization techniques) • Design, build, and operate scalable ELT pipelines using Snowpark and/or PySpark and advanced SQL to provision Gold datasets • Implement and evolve identity resolution logic mapping internal data to 3P identifiers (including LUIDs, RampIDs, TransUnion IDs), ensuring privacy-safe practices • Design and operate scalable data architectures across Snowflake and Databricks supporting batch and near real-time processing patterns • Build robust automated checks (e.g., Great Expectations or custom SQL assertions) and define quality standards to detect schema drift, null rate spikes, and volume anomalies • Lead performance optimization across platforms (query tuning, caching, incremental processing) and define and implement query tagging and chargeback models for accurate cost attribution • Establish monitoring, alerting, runbooks, and standard operating procedures to improve platform reliability and reduce incident time-to-resolution • Validate that output data adheres to privacy and business requirements, and define test strategies for partner-facing releases • Serve as the escalation point for diagnosing connection failures, data discrepancies, or latency issues with partner technical teams • Design and build internal AI agents (using frameworks like LangChain, Snowflake Cortex) and mentor other engineers through code reviews, design discussions, and operational best practices

Job Requirements

  • Bachelor’s degree or higher in Computer Science, Information Systems, Software, Electrical or Electronics Engineering
  • 5+ years of Data Engineering experience, with deep proficiency in advanced SQL and Python
  • 3+ years of hands-on experience with cloud data platforms, specifically Snowflake or Databricks
  • Proven experience building and operating scalable ELT pipelines using orchestration tools (e.g., Airflow, dbt)
  • Strong track record designing production-grade systems (observability, reliability, performance tuning, incident response)
  • Clean Room Knowledge: Exposure to Data Clean Room concepts and Clean Room platforms like LiveRamp, Snowflake or Databricks
  • AI/LLM Experience: Experience building applications with LLMs, RAG, Vector Databases, or frameworks like LangChain/LlamaIndex
  • Ability to mentor other engineers through code reviews, design discussions, and operational best practices
  • Certifications Preferred: SnowPro Core Certification OR Databricks Certified Data Engineer Associate
  • Certifications Highly Preferred: SnowPro Advanced: Data Engineer OR Databricks Certified Data Engineer Professional

Benefits

  • medical, dental and vision insurance
  • 401(k)
  • paid leave
  • tuition reimbursement
  • a variety of other discounts and perks

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