Databricks Solution Engineer

PassFort; Greater London; Presencial; GBP 70.000 - 110.000; Jornada completa

Descripción de la vacante

Moody's is seeking a senior Data/Analytics Engineer to design, build, and support scalable data and AI solutions on the Databricks Lakehouse Platform. The role involves developing governed datasets, data products, and robust data pipelines to enable advanced analytics and AI initiatives.

You will collaborate with business stakeholders and technical teams to translate requirements into scalable, cost-efficient solutions, while upholding security, governance, and performance standards across the

Formación

• 6+ years of experience in enterprise data roles including data engineering and analytics engineering.
• 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 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 pipelines, DevOps practices, and automation.
• Hands-on experience using AI tools to streamline workflows and enable responsible AI use.

Responsabilidades

• 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 to support reporting and AI initiatives.
• Partner with stakeholders to translate requirements into scalable, cost-effective solutions.
• Implement best practices for performance, security, data quality, compliance, and governance.
• Support integration of enterprise platforms like Salesforce, Power BI, Snowflake, and Fabric.
• Contribute to platform standards via CI/CD, automation, and DevOps.

Conocimientos

Data engineering

Analytics engineering

Solution engineering

AI concepts

SQL

Python

Apache Spark

Delta Lake

Data modeling

Data governance

Data quality

Enterprise data architecture

Git

CI/CD

Educación

Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or related field

Databricks Data Engineer Associate certification or higher

Databricks Generative AI Engineer Associate certification preferred

Herramientas

Databricks Lakehouse Platform

Apache Spark

SQL

Python

Delta Lake

Salesforce

Power BI

Snowflake

Microsoft Fabric

Git

CI/CD

Descripción del empleo

Skills And Competencies

• 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
• Databricks Generative AI Engineer Associate certification 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.