Senior Software Engineer — Backend, Data Products

Employment Type: Full-Time

Compensation: $200,000–$230,000 base salary, plus equity and benefits

Note: No C2C arrangements will be considered.

Any attempt to use personal or household contact information for solicitation, candidate submission, or vendor outreach is strictly prohibited and will be reported to LinkedIn.

About the Company

Our client is a well-funded, growth-stage AI company building an advanced enterprise analytics platform that helps major organizations understand which activities actually drive measurable business outcomes.

The company supports some of the world’s largest enterprises and operates a highly sophisticated data and computing environment. Its engineering organization is small, deeply technical, and focused on solving difficult problems across backend systems, data infrastructure, distributed computing, and applied AI.

About the Role

We are seeking a Senior Software Engineer — Backend, Data Products to join an independent, product-focused division responsible for building the customer-facing capabilities used to ingest, transform, validate, and operationalize complex enterprise data.

This is a hands‑on backend and data engineering role for someone who enjoys turning ambitious product ideas into resilient, composable production systems.

You will build the pipeline primitives, connectors, validation frameworks, orchestration services, APIs, and supporting infrastructure that allow customers and internal teams to work effectively with large volumes of messy, evolving data.

This is not a narrow ETL maintenance position. You will contribute across architecture, implementation, testing, deployment, observability, and production support. The environment moves quickly and is best suited to engineers who are comfortable with ambiguity, evolving priorities, rapid iteration, and substantial individual ownership.

What You’ll Do

• Build reusable pipeline primitives that enable data workflows to observe, match, act, and compose.


• Develop connectors and ingestion tooling for diverse and frequently changing data sources.


• Design transformation workflows that handle schema evolution and inconsistent real‑world data.


• Build validation and data‑quality controls directly into production pipelines.


• Design and ship backend services and GraphQL and REST APIs used by customers and internal teams.


• Develop maintainable API contracts, versioning strategies, and developer‑friendly interfaces.


• Orchestrate complex, multistep workflows using platforms such as Temporal.


• Build event‑driven systems using NATS, JetStream, Kafka, or comparable technologies.


• Design PostgreSQL schemas and optimize queries for correctness, maintainability, and performance.


• Partner with product, data science, and engineering teams to turn analytical workflows into reliable product capabilities.


• Improve system observability, debuggability, resilience, traceability, and developer experience.


• Participate directly in architecture, coding, testing, deployment, troubleshooting, and ongoing production support.

What We’re Looking For

• At least 5 years of professional software engineering experience.


• Deep production experience with Python.


• Strong knowledge of modern Python practices, including asynchronous programming, type hints, testing, and maintainable package design.


• Experience with libraries and frameworks such as pandas, SQLAlchemy, and Pydantic.


• Strong experience building resilient ETL or ELT pipelines at meaningful scale.


• Demonstrated ability to ingest, transform, validate, and troubleshoot complex datasets.


• Strong backend service and API design experience using GraphQL, REST, or both.


• Experience designing maintainable API contracts and versioning strategies.


• Advanced PostgreSQL experience, including schema design and query optimization.


• Comfort working with both ORM‑based data access and raw SQL.


• Experience building observable and fault‑tolerant production systems.


• Experience owning software through implementation, deployment, and production support.


• Ability to succeed in a fast‑moving, product‑focused startup environment.


• A hands‑on mindset and a strong preference for personally building and shipping production software.

Highly Preferred

• Experience with workflow orchestration platforms such as Temporal.


• Experience with NATS, JetStream, Kafka, or comparable event‑driven technologies.


• Familiarity with data‑quality and validation frameworks such as Great Expectations.


• Experience designing systems for correctness, traceability, and debuggability.


• Experience with Apache NiFi or similar data‑integration tooling.


• Familiarity with graph modeling, data lineage, or dependency tracking.


• Experience using AI‑assisted development tools as part of a modern engineering workflow.


• Performance‑sensitive development experience with Rust, C++, or another systems language.

Why This Opportunity

• Build central customer‑facing product capabilities rather than internal tooling alone.


• Solve difficult backend and data‑engineering problems involving large, complex enterprise datasets.


• Work with a small, highly technical engineering team.


• Have meaningful influence over architecture, implementation, and product direction.


• Join a well‑funded company with established enterprise adoption and significant growth momentum.


• Work in an environment that values technical autonomy, experimentation, curiosity, and practical execution.


• Receive a competitive base salary, meaningful equity, and comprehensive benefits.

This Role May Not Be the Right Fit If

• You are looking exclusively for low‑level systems or performance engineering work.


• You prefer managing engineers rather than personally building and shipping production software.


• You require fully established processes, detailed specifications, and fixed priorities.


• You are uncomfortable taking ownership when product requirements or technical priorities are still evolving.


• You are primarily interested in analytics or data science rather than production backend and data‑platform engineering.


• You are seeking a remote or hybrid position.

Work Authorization: Candidates must be currently authorized to work in the United States. This position is not eligible for new or future employer‑sponsored work authorization.