Assc Dir-Data Engineer

Moody's Corporation is a global leader in ratings and integrated risk assessment, focusing on transforming how the world sees risk. They are seeking a Senior Data Engineer to build and operate governed data pipelines, ensuring the delivery of trusted and compliant data products for business applications and analytics.

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)