Data Engineer
Role details
Job location
Tech stack
Job description
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.
Requirements
- 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.
Benefits & conditions
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, * Competitive Compensation: Including annual salary, pre-IPO stock options, and other financial compensation (if applicable)
- Medical, Dental, and Vision Coverage: 100% of premiums covered for you AND all of your dependents
- Unlimited Flexible Time Off: Unlimited FTO in addition to 12 company holidays per year, quarterly "recharge" days, and a week-long holiday break
- Home Office Reimbursement: To cover home office furniture and supplies, monthly home internet, and monthly cell phone (if applicable)
- Health & Wellness Reimbursement: To cover monthly gym membership or other qualifying expenses
- Parental Support: Generous parental and family leave, fertility benefits, and employer-sponsored stipends towards family forming services
- 401k Plan: To support you in your individual retirement goals
- Team Events: Frequent team-building events, fun team off-sites, and bi-annual company meetups
- Commitment to DEI: To prioritize Diversity, Equity, and Inclusion within our workplace and to stay true to our values and mission
- Mentorship and Training: To get you onboard quickly, learn new professional skills, and invest in your career development
- Impact and Visibility: To expose you to and provide the opportunity to work on highly strategic initiatives that will transform the business
- Encouragement and Empowerment: To explore and adopt new technologies and drive meaningful decisions and outcomes
- At Apartment List we believe that everyone deserves a home they love AND a career they love. We strive to build a diverse team that is a reflection of the people we serve; this is made possible through our commitment to fostering a culture of diversity, inclusion, equity, and connectedness., 168K-297K Annually Senior level 168K-297K Annually Senior level Blockchain * eCommerce * Fintech * Payments * Software * Financial Services * Cryptocurrency Design and maintain data architecture and pipelines to support compliance and risk teams. Build and optimize data models, standardize metrics, and create data dictionaries. Implement data quality, lineage monitoring, AI-driven agents for false-positive reduction and automation, and participate in on-call rotations to ensure SLAs are met. Top Skills: AirflowDatabricksDbtGitOmniPrefectPythonSnowflakeSQLTerraform Cash App, 168K-297K Annually Senior level 168K-297K Annually Senior level Blockchain * Fintech * Mobile * Payments * Software * Financial Services Lead design and optimization of data models and pipelines for compliance and risk; standardize metrics and documentation; build data quality, lineage, and monitoring (including AI agents for automation); manage ETL scheduling, on-call pipeline support, and collaborate with product and non-technical partners to translate business needs into automated, production-ready data solutions. Top Skills: AirflowDatabricksDbtGitOmniPrefectPythonSnowflakeSQLTerraform Fusion Risk Management, 135K-155K Annually Senior level 135K-155K Annually Senior level Professional Services * Software Lead architecture and buildout of a new graph-backed enterprise data platform: design ingestion, graph and relational storage, entity resolution pipelines, temporal models, ETL/ELT pipelines, governance, APIs, and production connectors. Ship scalable graph data models, traversal queries, and platform roadmap while enabling observability, security, and containerized deployments. Top Skills: AirflowAzureCypherDagsterDbtDockerGremlinHelmJavaKubernetesPythonSalesforceServicenowSparqlSQL
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