Senior Enterprise Data Engineer

ASPCA • New York, NY

1d • $138,000 - $143,000 • Remote

About The Position

The Senior Enterprise Data Engineer designs, builds, and maintains the ASPCA’s enterprise data warehouse ecosystem as part of the Enterprise Data Engineering Operations team in the Product, Data, and Reporting Solutions department. The role develops and maintains dbt Core models and data workflows across the medallion architecture, integrates master data management workflows into enterprise pipelines, and supports the organization’s transition from siloed systems to a centralized enterprise data solution. It ensures data assets are accurate, performant, reliable, and aligned with organizational standards.

The engineer works in a distributed, cross-functional environment and partners with stakeholders to deliver trusted, analytics-ready data. The position reports to the Director, Enterprise Data Engineering Operations and has no direct reports. It is remote-based and open to eligible candidates in the United States, with occasional off-hours support for critical data pipelines and travel of up to 5% as needed.

Requirements

• Expert-level dbt Core proficiency, including advanced model design, macro development, custom tests, documentation, performance optimization, and integration with automated deployment pipelines.
• Advanced proficiency with Microsoft Fabric and/or Azure Data Factory for enterprise orchestration, monitoring, scheduled and event-driven workflows, Lakehouse integration, operational support, and production pipeline troubleshooting.
• Deep knowledge of data warehousing principles, including dimensional modeling, medallion architecture, and ELT transformation patterns.
• Strong SQL skills.
• At least 5 years of hands-on experience building, maintaining, and optimizing production dbt Core transformation pipelines across medallion architectures.
• At least 5 years of experience designing, implementing, and supporting production data pipelines using Microsoft Fabric or Azure Data Factory, including orchestration, monitoring, operational support, and troubleshooting.
• At least 3 years of experience designing and maintaining data warehouse models and transformation workflows.
• At least 3 years of experience working in modern cloud data warehouse environments.
• High school diploma, GED, or equivalent experience.
• Required English language proficiency.
• Excellent analytical and problem-solving skills and a strong commitment to data quality.
• Ability to collaborate with technical and non-technical partners and communicate data and technical concepts clearly in writing and verbally.
• Comfort operating in a distributed, cross-functional environment and managing multiple priorities, changing requirements, and shifting timelines.
• Initiative, independence, curiosity, creativity, willingness to experiment and learn, openness to feedback, and commitment to teamwork and continuous improvement.
• Ability to exemplify ASPCA core values and behavioral competencies and contribute to an inclusive, collaborative team culture.
• Must be available for occasional off-hours support for critical data pipelines and willing to travel up to 5% as needed.

Nice To Haves

• Python experience.
• Familiarity with Git/GitHub workflows and DevOps CI/CD practices.
• Experience with cloud-native or SaaS-based data engineering tools.
• Proficiency with Snowflake, including warehouse configuration, performance tuning, query optimization, cost management, and role-based access controls.
• Familiarity with Snowflake-native dbt Projects, including development, deployment, scheduling, monitoring, configuration management, and dbt workload version upgrades within Snowflake.
• Experience applying dimensional and enterprise data modeling practices, such as star schemas, SCDs, and conformed dimensions.
• Experience integrating mastered entities and reference data from commercial MDM platforms into enterprise data pipelines; Reltio experience is preferred.
• Experience working within structured DevOps workflows, version control, and automated delivery pipelines.
• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related field.

Responsibilities

• Architect, implement, and maintain dbt Core models across the medallion architecture, applying transformation patterns for operational, analytical, and dimensional data requirements.
• Integrate MDM workflows and reference data into medallion-layer transformations in accordance with enterprise data governance standards.
• Apply mastered entities, harmonized identifiers, survivorship rules, and standardized reference values to Gold-layer models under enterprise MDM policies.
• Build data models for enterprise analytics, reporting, and downstream uses.
• Apply modeling best practices, including naming conventions, documentation, testing, and lineage tracking, to meet governance, quality, performance, and security requirements.
• Optimize SQL and dbt Core transformation logic for efficient, scalable, maintainable pipelines.
• Design, build, and maintain data ingestion, transformation, and delivery pipelines that meet engineering standards for code structure, documentation, and idempotent processing.
• Implement and maintain job orchestration, monitoring, alerting, automated testing, and error handling.
• Preserve version control for pipeline code artifacts and support CI/CD workflows for reliable deployment.
• Troubleshoot data quality and freshness issues across Microsoft Fabric, dbt Core, and Snowflake.
• Conduct root cause analysis and proactively improve pipelines.
• Work with the Data Management & BI team to align definitions, requirements, and expectations and ensure datasets are accurate, trusted, and analytics-ready.
• Collaborate with the Strategy & Research team to deliver granular, well-structured Silver-layer datasets for statistical analysis, data science modeling, and operational insights.
• Support data governance and quality through metadata practices and clear documentation of transformation logic.
• Identify opportunities to improve workflows, automate processes, and reduce technical debt.
• Participate in code reviews, knowledge-sharing sessions, and team initiatives that improve engineering quality and consistency.
• Evaluate emerging tools and technologies to advance the ASPCA’s data ecosystem.

Benefits

• Affordable health coverage, including medical, employer-paid dental, and optional vision coverage.
• Flexible time off, including vacation, paid personal time, sick time, bereavement time, paid parental leave, and 10 company-paid holidays.
• 401(k) plan with dollar-for-dollar employer matching up to 4%, plus an additional 4% employer contribution each year.
• Professional development opportunities, including classes, on-the-job training, coaching, mentorship, internal mobility, and opportunities to support work in the field.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: High school or GED