Senior Data Engineer

Posted Yesterday
Hiring Remotely in United States
Remote
149K-182K Annually
Senior level
Legal Tech • Database
Personal Injury Law Firm
The Role
Own end-to-end data engineering for a business domain, including API and other-source ingestion, dbt models, orchestration, data-quality testing, monitoring, documentation, and performance. Build reliable, AI-ready single sources of truth and ensure data freshness, accuracy, traceability, and scalability. Collaborate with stakeholders and the Director of Data, establish engineering patterns, review work, and mentor other engineers.
Summary Generated by Built In
Our Story

TopDog Law is not your typical law firm. We're a nationally scaling personal injury firm built for impact and growth — owning the client experience end-to-end, from marketing and intake through litigation. We believe that world-class marketing, paired with exceptional legal talent and operations, creates better experiences and outcomes for clients and the business alike.

Over the past three years, we've grown 2–3x year over year, setting a new standard on the marketing side of the personal injury space and proving what's possible when strategy, speed, and execution align. Now we're applying that same discipline and innovation to firm operations, case management, and national scale — intentionally building the infrastructure, systems, and teams to grow without sacrificing quality, culture, or accountability.

We are a fully remote team that share trust, open communication, and a commitment to doing great work. If you love ownership, thrive in a fast-moving environment, and want to help build something exceptional, you'll feel right at home here.


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.


What We Offer

  • 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.


Equal Opportunity Employer

We are an equal opportunity employer. Employment selection and related decisions are made without regard to age, race, color, national origin, religion, sex, disability, sexual orientation, gender identification, or being a qualified disabled veteran or qualified veteran of the Vietnam era or any other category protected by Federal or State law.
#LI-Remote


Skills Required

  • 5+ years building and maintaining production data pipelines
  • Expert-level dbt experience, including staging and mart architecture, incremental models, tests, macros, documentation, and exposures
  • Mastery of API-based data ingestion, including OAuth2 or API-key authentication, token refresh, pagination, rate limiting, retry/backoff, and incremental data assembly
  • Expertise with webhooks, file-based ingestion, databases, and CDC, including schema drift, idempotency, backfills, and incremental loading
  • Strong track record designing data-quality frameworks with freshness, volume, reconciliation, anomaly checks, and alerting
  • Strong Python for production extraction, loading, and tooling
  • Fluent SQL
  • Hands-on experience with a modern cloud data warehouse, preferably BigQuery or Snowflake
  • Experience architecting a clean, documented, AI-ready single source of truth
  • Experience with orchestration using Airflow, Dagster, or dbt Cloud jobs
  • Experience with Git in collaborative development environments
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The Company
HQ: Media, PA
76 Employees
Year Founded: 2019

What We Do

TopDog Law is a data-driven personal injury firm committed to maximizing results for our clients. By combining the strength of a trusted national brand with the expertise of experienced local attorneys, we deliver powerful legal representation to plaintiffs. Our data proves it: we consistently secure higher recoveries. Through cutting-edge technology and a streamlined legal platform, we make it easy for everyday people to get quality legal representation from virtually anywhere — all in one place.

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