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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Kids Inc - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $130,000.0 - $207,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Data Analysis, Automation of Tests, Continuous Integration, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Security, Datadog, Kubernetes, Data Analytics, Data Pipelines - **Published:** August 8, 2026 - **Apply:** https://jobs.gem.com/apartment-list/am9icG9zdDq2v4C-a-laznVqpaaXVFNi ## About the Role * 7+ years of data engineering experience, including a demonstrated track record of owning end-to-end pipeline architecture, not just implementing to spec. * Deep experience designing orchestration workflows in Apache Airflow, including making architectural tradeoffs across ingestion, transformation, modeling, and serving layers. * Experience working with containerized data infrastructure in production, including deploying services, diagnosing operational issues, and contributing to platform reliability and scalability. * Demonstrated ability to evaluate and communicate architectural tradeoffs (freshness vs. cost, scalability vs. simplicity) to both technical and non-technical stakeholders. * Experience building or significantly improving CI/CD practices for data pipelines, including automated testing, validation, and deployment. * A track record of leading incident response and monitoring strategy for a domain, including building alerting and observability ahead of failures rather than reacting to them. * Experience influencing technical decisions across multiple teams or functions, including partnering with engineering, product, or data science stakeholders outside your immediate team. * Experience mentoring other data engineers, including reviewing architectural and modeling decisions. Nice-to-haves: * Experience with Kubernetes-based data infrastructure * Experience leading a legacy ETL-to-modern-orchestration migration end-to-end, not just contributing to one. * Familiarity with observability and monitoring tooling such as Datadog at a platform-wide scale. * Experience building internal tooling or automation (including AI-assisted) that other engineers rely on. ## Description As Apartment List's data platform grows across more domains, more pipelines, and more stakeholders, the architectural decisions made today determine how much technical debt we're paying down in a year. We're looking for a Senior Data Engineer II (IC4) to own that architecture; end-to-end pipeline design, platform investment tradeoffs, and the technical judgment calls that keep the system reliable as it scales. This is not a design-from-the-whiteboard role. You'll still be hands-on-keyboard: writing pipelines, debugging production issues, and shipping code alongside the team. What sets this role apart is scope; you'll make architectural decisions independently, influence how Analytics Engineering, Data Science, and Engineering partners build on the platform, and be the person other data engineers come to when a design decision needs a second opinion. You'll work closely with Analytics Engineering, Data Science, and Engineering partners to shape how the data platform evolves. Here's what you'll do as part of the team * Own and evolve data pipeline architecture across core domains - ingestion, transformation, modeling, and serving - making project-level architectural decisions independently and evaluating tradeoffs between freshness, cost, scalability, and simplicity. * Lead the design and implementation of platform-level improvements: warehouse cost management, compute efficiency, and access control architecture, treating reliability, observability, and cost efficiency as core design constraints rather than afterthoughts. * Identify and lead technical initiatives that improve the platform's long-term health - proactively surfacing investments (orchestration, CI/CD, data access, developer experience) before they become blockers, and making the case for them. * Drive large, technically complex projects or multiple concurrent medium-sized initiatives that span teams, taking responsibility for outcomes rather than just execution. * Lead monitoring and testing strategy for your domain: proactively close observability gaps across the org, build alerting ahead of failures, and serve as the go-to engineer for the hardest production issues. * Influence technical decisions and architectural direction beyond the Data & Analytics team, partnering directly with EPD stakeholders on infrastructure decisions that affect their roadmaps. * Actively mentor other data engineers and analytics engineers, reviewing architectural and modeling decisions, and operate as a technical peer to senior engineers across teams. * Integrate AI meaningfully into data engineering workflows - building tooling and automation that creates leverage for the whole team, not just individual output, and coaching others on effective, validated use. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Debugging in the Dark](https://www.wearedevelopers.com/videos/1658-debugging-in-the-dark) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Software Engineering Social Connection: Yubo’s lean approach to scaling an 80M-user infrastructure](https://www.wearedevelopers.com/videos/1583-software-engineering-social-connection-yubo-s-lean-approach-to-scaling-an-80m-user-infrastructure) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)