Impress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Tailor your resume to this Backend Engineer — Data Pipeline role.
Rezi rewrites your resume against Sunset's job description. Free.
Tailor your resume to this Backend Engineer — Data Pipeline role.
Rezi rewrites your resume against Sunset's job description. Free.
Don't guess if your resume is good enough.
See how it scores against the Backend Engineer — Data Pipeline posting at Sunset — free, in seconds.
Don't guess if your resume is good enough.
See how it scores against the Backend Engineer — Data Pipeline posting at Sunset — free, in seconds.
About the Role
We are hiring a backend engineer to ensure the pipeline that de-identifies sensitive enterprise data is correct, replayable, operable, and safe to change. You will own the backend systems and contracts that make failure modes visible, preventable, and recoverable, working across asynchronous orchestration, batch workers, queues, object storage, databases, and various file formats.
Responsibilities
- Design and ship backend systems for multi-stage, high-volume data processing
- Define authoritative, versioned contracts for manifests, artifacts, lineage, and state transitions
- Make retries, checkpoints, partial failures, replay, backfills, migrations, and rollbacks safe and understandable
- Build independent reconciliation and verification instead of treating job success as proof of correct output
- Turn escaped and recurring failures into fixtures, regression coverage, release gates, and durable recovery paths
- Expose trustworthy run state and safe controls to the products people use to investigate and release data
- Diagnose production behavior across code, queues, stores, artifacts, data formats, and deployed versions
- Improve correctness, throughput, and operating leverage without weakening privacy, security, or release confidence
- Use AI deeply in development and in bounded verification systems, with explicit evaluation and independent checks
- Partner with machine learning, applied science, full-stack product, platform, security, and data engineering teammates
Requirements
- At least three years of professional software engineering experience, including personal ownership of production backend systems
- Strong in asynchronous or distributed systems and can reason precisely about queues, concurrency, state, storage, idempotency, partial failure, and recovery
- Worked on systems where output could be materially wrong even when every service looked healthy
- Define invariants and use reconciliation, control totals, diffs, replay, goldens, shadow paths, or independent sources to verify correctness
- Can design versioned data and artifact contracts and migrate them safely in a live system
- Debug from evidence across system boundaries and turn incidents into durable system improvements
- Choose technical work based on operator and customer consequences, not architecture in isolation
- Use modern AI engineering tools fluently, verify their output, and know when model-backed checks need deterministic guardrails and human review
- Communicate clearly across product, ML, data, platform, security, and customer-facing teams
Skills
- Asynchronous orchestration
- Batch workers
- Queues
- Object storage
- Databases
- File formats
- AI engineering tools
- Python
- AWS
- Airflow
- Batch
- SQS
- S3
- DynamoDB
- PostgreSQL
- Large-scale batch processing
- Workflow orchestration
- Event-driven systems
- Data movement
- Schema evolution
- Manifests
- Lineage
- CDC
- Migrations
- Reindexing
- Backfills
- Payments
- Ledgers
- Reconciliation
- Claims
- Fraud
- Identity
- Search quality
- Observability
- Sensitive data
- Multi-tenant data
- Least-privilege systems
- Auditability
- Quarantine
- Fail-closed release paths
- Deterministic checks
- Synthetic fixtures
- Offline replay
- Model-based judges
- Human review
Experience Level
- At least three years of professional software engineering experience
About the Company
- Sunset was founded to help founders, initially supporting startups through shutting down, and has expanded to unlock a new revenue stream for all businesses.
- The company's insight in 2025 was that the data generated daily through collaboration, communication, and building is valuable training data for AI models.
- Sunset partners directly with frontier AI labs, providing them with real, proprietary data grounded in actual business operations.
- The company has scaled from $0 to a multi-eight-figure run rate in months.
- Sunset has raised capital from investors including Floodgate, Afore, Ludlow, and Hustle Fund.