Databricks Solution Engineer

Moody; Greater London; On-site; GBP 110,000 - 140,000; Full time

Job summary

Moody’s is seeking a Databricks Solution Engineer to design, build, and support scalable data, analytics, and AI solutions on the Databricks Lakehouse Platform. You will work with enterprise stakeholders to translate requirements into scalable, cost-efficient data products.

The role requires 6+ years in data/analytics engineering, 4+ years on Databricks, and strong Spark, SQL, Python skills. You will integrate Salesforce, Power BI, Snowflake, and Fabric, while advancing CI/CD, governance, and

Qualifications

• 6+ years in data engineering, analytics engineering, solution engineering, or related disciplines within enterprise environments.
• 4+ years 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 ETL/ELT pipelines for scalable analytics and AI use cases.
• Knowledge of data modeling, governance, quality, and enterprise data architecture principles.
• Experience integrating Salesforce, Power BI, Snowflake, and Microsoft Fabric.
• Working knowledge of Git, CI/CD, DevOps, and automation frameworks.
• Proficient in AI concepts with hands-on AI tools to streamline workflows and responsible AI practices.

Responsibilities

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

Skills

Data engineering

Analytics engineering

Solution engineering

Apache Spark

SQL

Python

Delta Lake

AI concepts

Education

Bachelor's degree in Computer Science or related field

Databricks Data Engineer Associate certification or higher preferred

Tools

Databricks Lakehouse Platform

Salesforce

Microsoft Power BI

Snowflake

Microsoft Fabric

Git

Job description

Let's begin! Databricks Solution Engineer (14765)

• 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 artificial intelligence use cases
• Proven knowledge of data modeling, data governance, data quality management, and enterprise data architecture principles
• Experience integrating cloud and software-as-a-service platforms such as Salesforce, Microsoft Power BI, Snowflake, and Microsoft Fabric
• Working knowledge of Git, continuous integration and continuous delivery pipelines, DevOps practices, and automation frameworks
• Demonstrated proficiency in artificial intelligence concepts, with hands-on 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.
• Excellent communication, collaboration, and stakeholder management skills with the ability to translate business requirements into technical solutions

Education

• Bachelor's degree or equivalent qualification in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related field
• Databricks Data Engineer Associate certification or higher preferred

Responsibilities

Design, build, and support scalable data, analytics, and artificial intelligence solutions on the Databricks Lakehouse Platform.

• Design and implement scalable data and analytics solutions leveraging Databricks technologies
• Build, maintain, and optimize data pipelines using Apache Spark, SQL, Python, and Delta Lake
• Develop governed datasets and data products that support reporting, analytics, and artificial intelligence initiatives
• Partner with business stakeholders and technical teams to translate requirements into cost-effective and scalable solutions
• Implement best practices for performance optimization, security, data quality, compliance, and governance
• Support integration of enterprise platforms including Salesforce, Microsoft Power BI, Snowflake, Microsoft Fabric, and other business applications
• Contribute to platform standards through automation, continuous integration and continuous delivery practices, and DevOps initiatives
• Monitor, troubleshoot, and enhance solution performance to ensure reliability, scalability, and operational excellence

About the Team

Our Data and Analytics team is responsible for delivering trusted, scalable, and innovative data solutions that enable informed decision-making across Moody’s. The team partners closely with business and technology stakeholders to build modern data products, advance analytics capabilities, and drive the adoption of artificial intelligence technologies. By joining this team, you will contribute to high-impact initiatives focused on data modernization, operational efficiency, and responsible AI innovation across the organization.