Senior Data Engineer

About the role

• About Company ---

The Opportunity

We're hiring a Senior Data Engineer to own a business domain's data end-to-end, with a specific mandate: be the person who makes ingestion reliable and the numbers trustworthy.

You are expected to be the trusted authority on getting data in correctly and proving it's right for your division. You'll partner closely with the Director of Data to turn platform strategy into reliable production systems, and own the day-to-day reliability, performance, and scalability of what you build.

What You Will Own

Ingestion, End-to-End

Design and build how source data lands — third-party connectors, APIs, webhooks, file drops, CDC and batch loads.

Master API-based ingestion: authentication and token-refresh flows (OAuth2, API keys), pagination, rate-limit handling, retry and backoff, and reconciling incremental/paginated pulls into complete, correct datasets.

Own schema-drift handling, incremental vs. full-refresh strategy, idempotency and replayability, backfills, and late/duplicate-record handling.

Data Quality as a First-Class Deliverable

Build the tests, contracts, and monitoring that let stakeholders trust the numbers: freshness and volume checks, schema/type enforcement at the boundary, referential and uniqueness constraints, reconciliation against source-of-truth, and anomaly detection on business-critical metrics.

Ensure failures surface loudly and early — caught at the boundary, not discovered in a dashboard three days later.

Full Domain Delivery

Deliver the full pipeline for your domain: ingestion config, raw landing, dbt staging and mart models, data-quality tests, orchestration DAG, and runbook.

Stakeholders own the business definitions; you own translating them into correct, tested transformations — and you own the documentation that makes those definitions authoritative, traceable, and fuels our AI-ready environment.

Architecting an AI-Ready Single Source of Truth

Design domain data so it's clean, consistently grained, well-documented, and semantically unambiguous — the kind of SSOT that both dashboards and AI/agent-driven consumers can query reliably, without hidden business rules or hallucination.

Treat documentation and metric traceability as part of the deliverable, not an afterthought.

Platform Reliability & Performance

Implement monitoring, alerting, and observability across your pipelines and their platform dependencies.

Ensure data freshness and system uptime meet defined service expectations; optimize pipeline performance, compute utilization, and system efficiency.

Engineering Standards

Maintain version-controlled data infrastructure and CI/CD workflows for your pipelines.

Set the reference implementation others follow — especially for ingestion and DQ, where the team currently lacks a pattern.

Mentorship & Collaboration

Review other engineers' work, pair on hard problems, and raise the team's bar — senior impact shows up through others, not only your own commits.

Translate business needs into data solutions directly with your domain's stakeholders; understand not just how to build it but why the business needs it built that way.

What You Bring

• Required: 5+ years building and maintaining production data pipelines.
• Expert-level dbt — staging/mart architecture, incremental models, tests, macros, documentation, and exposures. This is non-negotiable.
• Mastery of API-based data ingestion — authentication and token-refresh (OAuth2, keys), pagination, rate limiting, retry/backoff, and assembling incremental pulls into complete, correct datasets.
• Demonstrated expertise across other ingestion source types (webhooks, files, databases/CDC), including schema drift, idempotency, backfills, and incremental loading.
• A strong track record designing data-quality frameworks — not a handful of not_null tests, but freshness/volume/reconciliation/anomaly checks and the alerting around them.
• Strong Python for custom extraction, loading, and tooling — able to build and maintain production ingestion code, not just glue scripts.
• Fluent SQL and hands-on experience with a modern cloud data warehouse (BigQuery or Snowflake preferred; comparable considered).
• Experience architecting a clean, documented, AI-ready single source of truth that downstream analytics and AI consumers can trust without hidden logic.
• Experience with orchestration (Airflow, Dagster, or dbt Cloud jobs) and with Git in collaborative development environments.

Who Thrives Here (Core Values)

• We don't hire on resumes alone. We hire for competence, character, and mindset.
• Embrace Change: Open to feedback, embracing change, and always asking "what's next?"
• Committed: You care deeply, have your teammates' backs, and show up to build something lasting.
• No-Ego Energy: Positive, professional, and solutions-oriented. Drama stays at the door.
• Ownership: You do what you say, follow through, and treat the business like it's yours.
• Fast & Hungry: You move with urgency, thrive under high expectations, and are motivated by growth and impact.

Base Salary

$148,800 and $181,700, commensurate with experience

Our job postings reflect the compensation range for the specific market and location of each role. Ranges vary by geography based on local market rates and cost of labor.

Benefits include

Medical, dental, and vision insurance, 401(k) with company match, HSA, life insurance, disability coverage, paid time off, and parental leave.