Offres d'emploi
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Senior Data Engineer (NYC Hybrid)
- United States
- United States
À propos
Partner with teams across the business and external partners to understand data needs and deliver reliable pipelines and models that solve real problems. Build and maintain scalable ingestion and egress pipelines in Airflow and dbt Cloud, ensuring high quality, automated data flows across cloud environments. Implement unit tests and monitoring to guarantee data integrity and reproducibility. Model and transform and structure healthcare datasets into usable formats that power data science models, and other reporting marts. Enhance and scale data models with SQL and dbt, ensuring precision and adaptability for new partnerships. Write Python code for Apache Airflow DAGs, components and utilities that orchestrate and monitor data workflows. Build complex pipelines that enable flexible scheduling, conditional logic, and smooth integration across multiple data sources. What you will bring
2+ years in data engineering or analytics engineering with proven ability to build pipelines and scalable workflows. Strong SQL skills for querying large, complex datasets. Proficiency in Python for data engineering tasks (transformations, APIs, automation). Experience with cloud data warehouses and storage (GCP preferred: BigQuery, Cloud Storage, Composer; AWS/Azure equivalents acceptable). Hands on experience with dbt or similar data modeling tools. Comfort working in collaborative dev/staging/prod environments, partnering with Product and Tech to safely test, launch, and anticipate the impact of new changes. Curiosity about operational workflows and a drive to partner with non‑technical teams, ensuring data and reporting align with how the business actually runs. You're not just a specification taker, you're part of the solution. A proactive, problem‑solving mindset and ability to thrive in fast‑paced, iterative environments. Strong communication skills to collaborate with analysts, engineers, and business stakeholders. Nice to have
Knowledge of healthcare data (claims, ADT feeds, eligibility files). Familiarity with Git/GitHub for version control. Early‑stage startup experience (seed/Series A), especially mission‑driven ones. Experience building semantic layers and data models in Looker (LookML). $120,000 - $160,000 a year The compensation range represents total earnings, including both base salary and target bonus. In addition to competitive base salary and bonus opportunities, we offer equity grants for qualifying roles, comprehensive medical, dental, and vision coverage, and a 401(k) retirement plan to support your long‑term financial well‑being. Empassion's philosophy is to provide competitive compensation that aligns with our mission, business, and employee needs while remaining financially responsible and applying it fairly, equitably, consistently, and transparently. We are a tech‑enabled remote healthcare company. We value the impact and significance of all team functions and roles equally, regardless of where you live. We plan to update our approach, data, and practices to ensure that we align with the market at year‑end 2025. This strategy ensures that our employees are paid fairly in the market for their skills, experience, and performance. We use current data to draft compensation numbers and will update the data yearly. Performance is a highly valued and meaningful driver of employee compensation within Empassion's market position. Our performance‑enhanced compensation philosophy rewards employees who consistently meet and exceed performance expectations through bonus incentives at all levels. We pay through consistent and compliant practices. We have team‑oriented goals and recognize performance against those goals through compensation. Everyone is an owner and is expected to add value and contribute; when Empassion wins, we all win. We are designed to fair and equitable and conduct a pay equity audit annually to ensure fair and equitable compensation level by level, job family by job family. Ready to Make a Difference?
If you’re driven by data, healthcare, and impact, apply and let’s talk!
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Compétences linguistiques
- English
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