Senior Data Engineer

About the Role We're looking for one person to own our data, start to finish. We don't split this work between a pipeline team and a reporting team, because every hand-off is a chance for numbers to drift. You'll pull data from the systems where it's created, model it into something people trust, and put it in front of the leaders who make decisions with it. You'll work alongside our architecture team and report to our principal architect, who built the platform and is ready to hand you real ownership of it. We run on open-source tooling in our own AWS environment rather than shipping data off to third-party platforms. That keeps costs in check and our data where we control it, and it means you'll actually engineer things instead of configuring connectors. Your first months focus on cleanup: retiring outdated history so every report reflects what's real today. From there, you'll design how each company we acquire brings its data onto our platform, so every integration goes faster than the last. We work hybrid out of Dallas because the best version of this role happens in the room. Sitting with finance or operations to understand what they need beats any requirements doc. About the Company We design, build and operate fiber networks that bring high-speed connectivity to entire communities. We're backed by venture investors and an infrastructure-focused private equity fund, and we're expanding into new markets and through acquisitions. We're a small team by choice, which means the work you ship shows up in how the business runs the following week. Key Responsibilities Own the data platform, built on Python, Airflow, dbt, Redshift and Postgres on AWS, and decide where it goes next Bring data from billing, finance, sales and operations systems into one source of truth Retire years of outdated historical data so every report reflects reality Build the dashboards and KPI reporting our CFO, controller, revenue, billing and operations leaders rely on Sit with stakeholders, define the metrics that matter, and refine based on their feedback Lead data migrations for companies we acquire, and turn each one into a repeatable playbook Scale processing jobs on Kubernetes when the workload calls for it Qualifications 7+ years building and running data systems in production You write Python and SQL every day, not just occasionally Hands-on experience with workflow orchestration (Airflow, Dagster or Prefect), a SQL transformation layer like dbt, and relational warehouses You've built the reporting layer yourself, not only the pipelines underneath it You're comfortable working face to face with finance and operations leaders, and you'd rather ask the question than guess Based in the Dallas-Fort Worth area, with office time ideally weekly and at least a couple of times a month Authorized to work in the U.S. without sponsorship Bonus Points You've migrated or consolidated data after an acquisition or major system change Experience with Redshift, Metabase or other self-hosted, open-source tooling Terraform, Docker, or data quality and observability frameworks You've been one of the only data people at a startup or growth-stage company What We Offer $165,000-$190,000 base plus a 10% annual bonus Hybrid schedule with a flexible in-office cadence Full ownership of a data function at a company in growth mode Direct access to executive leadership and real influence on how the business makes decisions Work tied to physical infrastructure that changes how communities connect A straightforward hiring process: an intro conversation, a hands-on Python and SQL session with the person you'd report to, then time with the broader team Strategic Employment