Databricks Lakehouse Engineer - AI-Driven Data Solutions

Moody's Investors Service

Greater London

On-site

GBP 95,000 - 125,000

Full time

14 days+

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Job summary

Moody’s Investors Service is seeking a senior data/analytics engineer to design, build, and support scalable AI-enabled data solutions on the Databricks Lakehouse Platform. You will craft end-to-end data pipelines, governance, and data products to empower reporting and insights.

The role requires 6+ years in data/analytics engineering and hands-on Databricks experience, plus strong Spark, SQL, Python, and Delta Lake skills.

Qualifications

6+ years of experience in Data Engineering, Analytics Engineering, Solution Engineering, or related disciplines within enterprise environments.
4+ years of hands-on experience designing and implementing solutions on the Databricks Lakehouse Platform.
Strong expertise in Apache Spark, SQL, Python, Delta Lake, and modern data engineering practices.
Experience building and optimizing Extract, Transform, Load and Extract, Load, Transform data pipelines for scalable analytics and AI use cases.
Proven knowledge of data modeling, data governance, data quality management, and enterprise data architecture principles.
Experience integrating cloud and SaaS platforms such as Salesforce, Power BI, Snowflake, and Fabric.
CI/CD pipelines, DevOps practices, and automation frameworks.
Proven AI proficiency with hands-on experience using AI tools to streamline workflows and ethical AI use.
Excellent communication, collaboration, and stakeholder management skills.

Responsibilities

Design, build, and support scalable data, analytics, and AI solutions on the Databricks Lakehouse Platform.
Design and implement scalable data and analytics solutions leveraging Databricks technologies.
Build, maintain, and optimize data pipelines using Spark, SQL, Python, and Delta Lake.
Develop governed datasets and data products supporting reporting, analytics, and AI initiatives.
Partner with business stakeholders and technical teams to translate requirements into scalable solutions.
Implement best practices for performance optimization, security, data quality, compliance, and governance.
Support integration of enterprise platforms including Salesforce, Power BI, Snowflake, Fabric, and other apps.
Contribute to platform standards through automation, CI/CD, and DevOps initiatives.
Monitor, troubleshoot, and enhance solution performance for reliability and scalability.