Senior Data Engineer

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<div><strong style="background-color: transparent; color: rgb(0, 0, 0);">Who we are</strong></div><div><br></div><div><span style="background-color: transparent; color: rgb(0, 0, 0);">Apartment List is the premier rental matchmaker, connecting ready-to-move renters with compatible city properties.  Our renters benefit from cutting-edge technology and a personalized approach when we match them with curated properties that fit their wishlist.  Meanwhile, our supply partners harness our generative AI and machine learning to efficiently connect with our qualified renters.  With performance-based pricing, our partners’ success is our success as we strive to deliver renters a home they love at the value they deserve.</span></div><div><br></div><div><strong style="background-color: transparent; color: rgb(0, 0, 0);">About the Role</strong></div><div><br></div><div><span style="background-color: transparent; color: rgb(0, 0, 0);">We are seeking a Senior Data Engineer (L3) to help build and operate the reliable, scalable data systems that power analytics, experimentation, and decision-making across Apartment List. In this role, you will be a strong end-to-end executor responsible for delivering production-grade data pipelines and workflows that meet defined service-level agreements (SLAs) for freshness, quality, and cost.</span></div><div><br></div><div><span style="background-color: transparent; color: rgb(0, 0, 0);">You will work closely with Analytics Engineering, Data Science, Product, and Engineering partners to deliver durable data platform improvements that support company-wide initiatives. The ideal candidate is comfortable owning medium-sized data platform projects end-to-end—from design through deployment and operational support—while working within established platform architecture and engineering patterns.</span></div><div><br></div><div><span style="background-color: transparent; color: rgb(0, 0, 0);">This role emphasizes execution excellence, reliability, and operational ownership within existing platform standards. Platform-level architecture and system design are owned at more senior levels, but this role plays a critical part in ensuring that the platform functions reliably at scale.</span></div><div><br></div><h3><strong style="background-color: transparent; color: rgb(0, 0, 0);">Responsibilities</strong></h3><div><br></div><ul><li class=""><span style="background-color: transparent;">Design, build, test, and deploy scalable and reliable data pipelines that power analytics and product decision-making.</span></li><li class=""><span style="background-color: transparent;">Own medium-sized data platform initiatives end-to-end, from initial design through production deployment and operational support.</span></li><li class=""><span style="background-color: transparent;">Design, migrate, and maintain data workflows in Apache Airflow, including supporting migration of legacy ETL systems to modern orchestration patterns.</span></li><li class="">Ensure pipeline reliability by proactively monitoring workflow SLAs for freshness, quality, and performance, and resolving failures efficiently.</li><li class="">Implement and utilize monitoring systems to detect pipeline failures, schema drift, and data quality anomalies.</li><li class="">Participate in on-call rotations and contribute to incident response and root cause analysis for data incidents.</li><li class="">Apply best practices in warehouse performance and cost optimization, including partitioning, indexing, and efficient data modeling to control BigQuery spend.</li><li class="">Build maintainable, modular data models and pipelines using reusable patterns and shared components across the team.</li><li class="">Partner closely with Analytics Engineering, Data Science, and business stakeholders to deliver durable improvements across the ingestion, transformation, modeling, and serving layers of the data platform.</li><li class="">Contribute to operational excellence through documentation, monitoring improvements, and participation in postmortems and reliability initiatives.</li></ul><div><br></div><h3><strong style="background-color: transparent; color: rgb(0, 0, 0);">Key Qualifications & Competencies</strong></h3><div><br></div><ul><li class=""><span style="background-color: transparent;">5+ years of experience in data engineering, with a track record of delivering reliable production data pipelines and systems.</span></li><li class=""><span style="background-color: transparent;">Strong experience designing and maintaining orchestration workflows using </span><strong style="background-color: transparent;">Apache Airflow</strong><span style="background-color: transparent;">.</span></li><li class=""><span style="background-color: transparent;">Experience building scalable data pipelines using modern cloud data platforms such as </span><strong style="background-color: transparent;">BigQuery</strong><span style="background-color: transparent;"> and tools such as </span><strong style="background-color: transparent;">DBT</strong><span style="background-color: transparent;">.</span></li><li class=""><span style="background-color: transparent;">Strong understanding of data modeling, schema design, and building maintainable, modular data systems.</span></li><li class=""><strong style="background-color: transparent;">Experience implementing CI/CD best practices for data pipelines</strong><span style="background-color: transparent;">, including automated testing, validation, and deployment workflows to ensure reliable and repeatable production releases.</span></li><li class=""><span style="background-color: transparent;">Experience monitoring and operating production data systems, including pipeline observability, data quality checks, and incident response.</span></li><li class=""><span style="background-color: transparent;">Ability to identify performance and cost risks in large-scale data systems and implement optimizations.</span></li><li class=""><span style="background-color: transparent;">Strong collaboration skills and experience working with cross-functional partners including analytics engineers, data scientists, and product teams.</span></li><li class=""><span style="background-color: transparent;">Proven ability to independently execute medium-sized projects and deliver reliable, production-grade systems.</span></li></ul><div><br></div><h3><strong style="background-color: transparent; color: rgb(0, 0, 0);">Nice-to-haves</strong></h3><div><br></div><ul><li class=""><span style="background-color: transparent;">Familiarity with Kubernetes-based data infrastructure, including deploying and operating containerized data services and workflows in a production environment.</span></li><li class=""><span style="background-color: transparent;">Experience migrating legacy ETL systems to modern orchestration frameworks.</span></li><li class=""><span style="background-color: transparent;">Familiarity with observability and monitoring tools for data pipelines (e.g., Datadog or similar).</span></li><li class=""><span style="background-color: transparent;">Experience operating data systems with strict SLAs for freshness, reliability, and cost efficiency.</span></li></ul><div><br></div><h3><strong>Here's the Pay Range:</strong></h3><div><br></div><div>At Apartment List, we carefully consider a variety of factors to determine compensation for each position, including the role, level, and work. The US Total Target Compensation (TTC) for this position is:</div><div><br></div><ul><li class="">Zone 1: $148,000 - $180,000 TTC (including $133,000 - $158,400 base salary) + equity</li><li class="">Zone 2: $137,000 - $167,000 TTC (including $123,000 - $147,000 base salary) + equity</li><li class="">Zone 3: $126,000 - $153,000 TTC (including $113,000 - $135,000 base salary) + equity</li></ul><div><br></div><div>This reflects the compensation target for new hire salaries for the position across all US locations. Please note, the compensation details provided do not include benefits and perks that we offer. </div><div><br></div><div>We also rely on market indicators along with considering your work location, job related skills, experience and relevant education and training, to determine compensation that is fair and competitive for you. Apartment List will consider paying compensation near the higher of the range in exceptional circumstances, where candidates have the experience, credentials or expertise that would warrant such consideration. It is always our goal to hire exceptional talent and we would be happy to share more about compensation during the hiring process.</div><div><br></div>

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