• Ensure the accurate, reliable, and consistent collection of data across diverse platforms and products • Design and enforce tracking governance, ensuring data integrity • Oversee the entire data lifecycle of tracking events • Empower teams to utilize data autonomously • Contribute to Docplanner’s data-driven culture and operational efficiency • Streamline and consolidate existing tools to create a more efficient data ecosystem

Who we are 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. About the Role 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. 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. 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. Responsibilities - Design, build, test, and deploy scalable and reliable data pipelines that power analytics and product decision-making. - Own medium-sized data platform initiatives end-to-end, from initial design through production deployment and operational support. - Design, migrate, and maintain data workflows in Apache Airflow, including supporting migration of legacy ETL systems to modern orchestration patterns. - Ensure pipeline reliability by proactively monitoring workflow SLAs for freshness, quality, and performance, and resolving failures efficiently. - Implement and utilize monitoring systems to detect pipeline failures, schema drift, and data quality anomalies. - Participate in on-call rotations and contribute to incident response and root cause analysis for data incidents. - Apply best practices in warehouse performance and cost optimization, including partitioning, indexing, and efficient data modeling to control BigQuery spend. - Build maintainable, modular data models and pipelines using reusable patterns and shared components across the team. - 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. - Contribute to operational excellence through documentation, monitoring improvements, and participation in postmortems and reliability initiatives. Key Qualifications & Competencies - 5+ years of experience in data engineering, with a track record of delivering reliable production data pipelines and systems. - Strong experience designing and maintaining orchestration workflows using Apache Airflow. - Experience building scalable data pipelines using modern cloud data platforms such as BigQuery and tools such as DBT. - Strong understanding of data modeling, schema design, and building maintainable, modular data systems. - Experience implementing CI/CD best practices for data pipelines, including automated testing, validation, and deployment workflows to ensure reliable and repeatable production releases. - Experience monitoring and operating production data systems, including pipeline observability, data quality checks, and incident response. - Ability to identify performance and cost risks in large-scale data systems and implement optimizations. - Strong collaboration skills and experience working with cross-functional partners including analytics engineers, data scientists, and product teams. - Proven ability to independently execute medium-sized projects and deliver reliable, production-grade systems. Nice-to-haves - Familiarity with Kubernetes-based data infrastructure, including deploying and operating containerized data services and workflows in a production environment. - Experience migrating legacy ETL systems to modern orchestration frameworks. - Familiarity with observability and monitoring tools for data pipelines (e.g., Datadog or similar). - Experience operating data systems with strict SLAs for freshness, reliability, and cost efficiency. Here's the Pay Range: 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: - Zone 1: $148,000 - $180,000 TTC (including $133,000 - $158,400 base salary) + equity - Zone 2: $137,000 - $167,000 TTC (including $123,000 - $147,000 base salary) + equity - Zone 3: $126,000 - $153,000 TTC (including $113,000 - $135,000 base salary) + equity 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. 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.

Role Description The Financial Services Division is seeking a Data Services Specialist to support a high-volume Data Services Department. The ideal candidate will possess strong data entry skills, comply with our service level agreements, meet assigned performance metrics, and apply great attention to detail while processing data to ensure accurate information is captured in organization records. We are looking for a team player who is able to work independently and according to departmental and organizational guidelines. - Nimble Membership processing - Direct Mail Process (DMP) Review - Daily Mail processing/review - Assisting with monthly miscellaneous projects as needed Qualifications - High School Degree required - 4 years of data entry experience required - Strong Microsoft Office Suite skills - Ability to successfully multi-task - Attention to detail - Demonstrated communication skills, both written and verbal Benefits - Industry competitive base pay ranging from $40,000 - $46,000 for this role - A culture of recognition including new hire welcome announcements, service anniversary awards, referral bonuses, monthly All Employee Assembly, appreciation awards - Generous Paid Time Off, including holidays, vacation days, personal days and sick days - Comprehensive benefits package including medical, dental, vision, Flexible Spending Accounts (FSA), disability & life insurance, pet insurance and retirement savings - Guided by our mission, we provide top tier diabetes supply coverage through our medical benefits program - A company focus on offering mental health programs and work/life balance with most of our employees working remote - Joining our dedicated team affords the gratification of knowing beyond a doubt that you will impact the lives and well-being of millions

Design and implement scalable data architectures for high-volume IoT data processing, optimize data pipelines for AI workloads, and collaborate with cross-functional teams to enhance data workflows and insights for industrial applications.