Assc Dir-Data Engineer

Moody's is a global leader in ratings and integrated risk assessment, focused on transforming how the world sees risk. They are seeking an Associate Director of Data Engineering to build and operate governed Databricks Lakehouse pipelines, ensuring reliable data products and access for business applications while mentoring other engineers in the team.

Responsibilities:

• Build and operate governed Databricks Lakehouse pipelines (DLT/dbt) orchestrated via MWAA to deliver trusted, compliant data products
• Provide access to usable data for Corps and Gov business applications, embedded analytics, and ad-hoc stakeholder requests
• Own the ‘pipes’ that enable downstream use cases—reliable ingestion, transformation, and delivery patterns that support customer-facing risk solutions
• Design, build, and operate production Delta Live Tables (DLT) pipelines to improve data freshness, quality, and operational resilience
• Implement transformations, testing, and validation using dbt, SQL, and Spark/Python to ensure accuracy, consistency, and trust
• Orchestrate and monitor workflows using AWS MWAA (Airflow) and Databricks Workflows, implementing alerting, retries, backfills, and runbook-driven operations
• Build robust infrastructure and reusable frameworks that allow stakeholders to create predictive and prescriptive analytics (and ML) on top of platform data
• Enable open configurations and patterns so product and engineering teams can embed analytics and pipelines within their own code repositories safely and consistently
• Drive technical design and execution for key initiatives; clarify scope, identify risks, and deliver iteratively in ambiguous problem spaces
• Improve existing systems through iterative, non-disruptive refactoring (backwards-compatible changes, staged migrations, measurable improvements)
• Mentor other engineers and contribute to engineering standards and the technical vision of the CnG Data and AI Platform

Requirements:

• Proven senior-level data engineering experience designing and operating data products on the Databricks Lakehouse (Delta Lake) in regulated environments
• Hands-on experience building and running Databricks Delta Live Tables (DLT) in production, including incremental/near-real-time patterns, expectations, and operationalization
• Strong orchestration experience using AWS MWAA (Managed Workflows for Apache Airflow) and Databricks Workflows to schedule, monitor, and recover pipelines
• Expert SQL plus strong Python/Spark skills; deep experience implementing transformations and tests using dbt
• Strong DataOps mindset: CI/CD for data, data observability/monitoring, incident triage, performance tuning, and designing for reliability and auditability
• Literacy in Machine Learning concepts and workflows (e.g., feature generation, training/serving considerations), with the ability to partner effectively with ML engineers/data scientists and ensure responsible use
• Experience using AI tools to streamline workflows and enhance operational efficiency. Proven ability to implement AI-powered solutions to solve business challenges. Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use
• Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience)