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UO
UJA-Federation of New York
Data Engineer, Data and Insights
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Based on New York data
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What they do
A Data Engineer designs, builds and manages the information or big data infrastructure. Develops the architecture that helps analyze and process data in the way the organization needs it. Makes sure those systems are performing smoothly.
$115,876 / year median in New York
+8% projected growth
Job Description
UJA-Federation of New York is the world's largest local philanthropy. We focus on caring for people in need and inspiring the Jewish future. The Data Engineering team at UJA-Federation of New York is seeking an experienced Data Engineer to join us. The ideal candidate will bring strong expertise in Python development for data-intensive applications, including hands-on proficiency with SQL and PySpark. This role involves building scalable data pipelines, improving data quality and reliability, and collaborating with cross-functional teams to support analytics, reporting, and machine learning initiatives. Key Responsibilities Design, build, and maintain robust ETL/ELT pipelines and data workflows using Python. Implement best practices for data architecture, modeling, and processing at scale. Collaborate with team members to leverage Azure DevOps for CI/CD, release management, and automated testing. Ensure compliance with data governance, quality, and security standards. Mentor junior engineers and contribute to the growth of engineering best practices. Partner with stakeholders (data scientists, analysts, business teams) to deliver reliable data solutions. Qualifications 5+ years of professional experience in data engineering or related roles. Strong proficiency in Python, with proven experience in data-focused libraries (e.g., PySpark, Pandas). Hands-on experience designing and consuming RESTful APIs or GraphQL endpoints. Proficiency in SQL and relational databases (e.g., SQL Server, PostgreSQL, MySQL). Solid experience with data lakes and data warehouses. Familiarity with cloud environments is a plus, with Azure experience preferred. Familiarity with Microsoft Fabric (Data Lakehouse, Fabric pipelines, or Fabric Data Warehouses) is a strong plus. Hands-on experience with Azure DevOps tools: pipelines, repositories, boards, and artifacts. Strong knowledge of CI/CD pipelines and version control (Git). Excellent problem-solving, communication, and collaboration skills. Preferred Skills Exposure to machine learning workflows and MLOps practices. Experience using donor management systems (Salesforce NPSP in particular). Knowledge of containerization a plus (Docker/Kubernetes). Some familiarity with Infrastructure as Code (IaC) tools such as Terraform, Bicep, or ARM templates is a bonus.