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Clear Street
Clear Street
201 – 500 Employees
H1B Visa SponsorConsultingFinanceLogistics
Clear Street develops financial infrastructure for institutional clients, combining clearing, custody, execution, and prime brokerage capabilities in one platform. Its cloud-native technology is designed to replace legacy financial systems and provide a unified operating foundation across asset classes, countries, and currencies. The company brings together teams working across finance, technology, and related operational disciplines to modernize how institutions manage complex global markets.
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Senior Data Engineer, Remote (United States)

Lead reliable data pipelines, dbt models, and governance for Clear Street’s cloud-based brokerage and trading platform. Keep marketing, customer lifecycle, and regulated brokerage data accurate from collection through use.

USUnited States
$150,000 – $250,000 / year
RemoteFull-timeSeniorEnglish RequiredData Engineer
CloudETLKubernetesPythonSQL

Description

  • Build and manage data systems for growth, customer lifecycle journeys, and brokerage operations.
  • Ingest spend, clicks, conversions, and related data from paid, affiliate, organic, application, CRM, support, and brokerage systems.
  • Reconcile marketing and brokerage data with authoritative systems of record.
  • Send funded-account outcomes and other conversion data to advertising platforms.
  • Connect customer identity across the journey from anonymous visit through sign-up, KYC, funding, and first trade.
  • Keep lifecycle messaging, CRM, and support systems synchronized with actual customer events.
  • Model account opening, KYC, funding, transfers, trading, and settlement data to regulated broker-dealer standards.
  • Ensure inbound feeds are complete and timely, and outbound data syncs are delivered correctly.
  • Manage dbt warehouse layers, including raw, staged, identity-resolved, and curated models.
  • Define data contracts with product engineering and external platform owners.
  • Manage governance for role-based access, PII masking, retention, auditability, and self-service permissions.
  • Select batch, change-data-capture, or streaming approaches to fit consumer needs.
  • Work with Marketing, Product, and Operations to define required events and fields.
  • Collaborate with engineering and infrastructure teams responsible for trading systems, the core clearing ledger, cloud, Kubernetes, and networking.

Requirements

  • At least five years in data engineering or analytics engineering, including responsibility for production pipelines when they fail.
  • Strong working knowledge of SQL and Python.
  • Production dbt experience with layered raw, staged, and curated warehouse models, defined grains, tests, and incremental builds.
  • Hands-on experience ingesting third-party and application data through managed connectors, event pipelines, and change-data-capture.
  • Experience addressing schema drift, resynchronizations, duplicates, and late or missing records.
  • Experience delivering data through reverse ETL, audiences, or conversion feeds, and ensuring its accuracy after export.
  • Experience reconciling against systems of record, monitoring freshness and volume, and preventing recurring incidents.
  • Experience with role-based access, PII masking, retention, and auditable data governance.
  • Familiarity with fintech or brokerage data, including account opening and KYC, funding and transfers, trades, and settlement.
  • Self-directed approach and ability to work effectively without a large escalation team.

Benefits

  • Competitive pay, benefits, and perks.
  • Company equity.
  • 401(k) matching.
  • Gender-neutral parental leave.
  • Comprehensive medical, dental, and vision insurance.
  • Lunch stipends.
  • Fully stocked kitchens.
  • Team happy hours.
  • Chance to join a small, growing team.
  • A modern, high-quality codebase with little technical debt and scope to build services and features.
  • Merit-based culture that values collaboration.

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