Senior Data Engineer

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Zócalo Health

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2021

📡 Telecommunications

🌍 Social Impact

Healthcare • Telecommunications • Social Impact

Zócalo Health is a primary care group aimed at improving patient experiences and access to healthcare for Latino communities. They provide culturally competent, integrated whole-person care, connecting complex and high-risk patients with dedicated care teams that include local health outreach specialists. Zócalo Health emphasizes building lasting relationships within the community and offers a combination of in-person and virtual services to cater to the unique medical, social, and mental health challenges of its members.

📋 Description

• Build and operate production-grade ingestion pipelines from core clinical, operational, and third-party systems into our Databricks lakehouse • Develop and maintain dbt models that turn raw data into clean, well-documented, analytics-ready datasets • Establish data quality, testing, and monitoring practices that make pipelines reliable and trustworthy • Help shape ingestion patterns and architecture standards alongside the Principal Data Engineer • Enable company-wide metrics for care outcomes and operations • Collaborate with cross-functional leads to develop and iterate on a suite of core operational dashboards, ensuring teams have the self-service tools they need to track company metrics and outcomes. • Design, build, and operate production data pipelines across clinical, operational, and third-party systems using API-based ingestion, Change Data Capture (CDC), and event- or webhook-driven patterns • Build and maintain transformation layers in dbt, including tests, documentation, and reusable models • Develop and refine core analytical and longitudinal data models used across the company • Implement testing, monitoring, and observability to ensure data quality, pipeline reliability, and system performance • Apply strong engineering fundamentals to improve the scalability, performance, and cost-efficiency of data systems on AWS and Databricks • Partner with Product to support metric definitions, outcome measurement, and reporting needs • Contribute to engineering standards, code review, and a culture of knowledge sharing and continuous improvement • Partner with business, product, and engineering stakeholders to design and build intuitive data visualizations and dashboards that drive actionable insights and program visibility.

🎯 Requirements

• 5+ years of experience in data or backend engineering roles with significant data platform responsibility • Hands-on experience building and operating production-grade data pipelines and ingestion frameworks • Strong proficiency in SQL and Python for data ingestion, processing, and transformation • Experience with a cloud data platform; experience with AWS and Databricks (or a comparable Spark-based lakehouse) strongly preferred • Experience building SQL-based transformation workflows; hands-on experience with dbt preferred • Strong computer science fundamentals, including comfort reasoning about distributed systems and data processing at scale • Ability to diagnose and resolve performance, reliability, and data quality issues in complex systems • Strong ownership mindset and comfort operating in ambiguous, fast-growing environments • Clear communicator able to partner effectively with technical and non-technical stakeholders • Experience building dashboards or analytical outputs used by executives and frontline teams.

🏖️ Benefits

• Equity compensation package • Comprehensive benefits including medical, dental, and vision • 401k • Flexible PTO policy - take the time you need to recharge • $1,000 home office stipend • We provide the equipment needed for this role. • Opportunity for rapid career progression with plenty of room for personal growth.