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Remote Senior Backend Engineer, Data Pipelines and Integrationsgrabjobs • United States
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Remote Senior Backend Engineer, Data Pipelines and Integrations

grabjobs
  • US
    United States
  • US
    United States
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Über

About the Role We are looking for a
Senior Backend Engineer
to own the systems that transform our unified dataset into application-ready content and
robust downstream analytics . This role bridges the gap between core datasets and end-user experiences by building the pipelines, services, and models that make our content discoverable, searchable, analyzable, and operationally reliable.
Your work will power both the product and the business: organizing content into application-ready structures; managing fine-grained usage events; building ETLs that support reporting, billing, and analytics; and developing fingerprinting pipelines for deduplication, rights attribution, and safety. You will architect systems that ensure our data remains consistent across ingestion, application surfaces, and downstream consumers.
You will collaborate closely with Product, ML Research, Analytics, and Infrastructure teams, working with tools such as
BigQuery ,
Dataflow/Beam ,
PubSub , and internal microservices. Experience designing data models that support real-time features, retrieval, and analytics is strongly valued.
What You’ll Do
Design and maintain application-level data models
that organize rich content into canonical structures optimized for product features, search, and retrieval.
Build high-reliability ETLs and streaming pipelines
to process usage events, analytics data, behavioral signals, and application logs.
Develop data services
that expose unified content to the application, such as metadata access APIs, indexing workflows, and retrieval-ready representations.
Implement and refine fingerprinting pipelines
used for deduplication, rights attribution, safety checks, and provenance validation.
Own data consistency
between ingestion systems, application surfaces, metadata storage, and downstream reporting environments.
Define and track key operational metrics , including latency, completeness, accuracy, and event health.
Collaborate with Product teams
to ensure content structures and APIs support evolving features and high-quality user experiences.
Partner with Analytics and Research teams
to deliver clean usage datasets for experimentation, model evaluation, reporting, and internal insights.
Operate large analytical workloads
in BigQuery and build reusable Dataflow/Beam components for structured processing.
Improve reliability and scale
by designing robust schema evolution strategies, idempotent pipelines, and well-instrumented operational flows.
What We’re Looking For
Experience building
ETL/ELT pipelines
, event processing systems, and structured data models for applications or analytics.
Strong background in
data modeling
, metadata systems, indexing, or building canonical representations for heterogeneous content.
Proficiency in
Python
, SQL, and scalable data-processing frameworks (Dataflow/Beam, Spark, or similar).
Familiarity with
BigQuery
or other analytical data warehouses and strong comfort optimizing large queries and schemas.
Experience with
event-driven architectures
, Pub/Sub, or Kafka-like systems.
Strong understanding of
data quality
, schema evolution, lineage, and operational reliability.
Ability to design pipelines that balance
cost, latency, correctness, and scale
.
Clear communication skills and an ability to collaborate closely with Product, Research, and Analytics stakeholders.
Nice to Have
Experience building
application-facing APIs
or microservices that expose structured content.
Background in
information retrieval
, indexing systems, or search infrastructure.
Experience with
fingerprinting
, perceptual hashing, audio similarity metrics, or content-matching algorithms.
Familiarity with
ML workflows
and how downstream analytics and usage data feed back into research pipelines.
Understanding of
batch + streaming architectures
and how to blend them effectively.
Experience with Go, Next.js, or React Native for occasional full-stack contributions.
Why Join Us
You will design the
core data services and pipelines
that power our product experience, analytics, and business operations.
You’ll work on high-impact data challenges involving real-time signals, large-scale metadata systems, and cross-platform consistency.
You’ll join a small, fast-moving team where you’ll shape the structure, reliability, and intelligence of our downstream data ecosystem.
Benefits
Highly competitive salary and equity
Quarterly productivity budget
Flexible time off
Fantastic office location in Manhattan
Productivity package, including ChatGPT Plus, Claude Code, and Copilot
Top notch private health, dental, and vision insurance for you and your dependents
401(k) plan options with employer matching
Concierge medical/primary care through
One Medical
and
Rightway
Mental health support from
Spring Health
Personalized life insurance, travel assistance, and many other perks
Udio’s success hinges on hiring great people and creating an environment where we can be happy, feel challenged, and do our best work.
Udio provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, or gender expression. We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities.
This role is eligible for a compensation package of base salary, equity, and benefits. The starting base salary range for this role is $160,000 - $220,000. Actual salary may vary based on level, work experience, performance, and other factors evaluated during the hiring process.
  • United States

Sprachkenntnisse

  • English
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