Senior Databricks Lakehouse Solutions Engineer

Moody's Corporation

Greater London

Hybrid

GBP 80,000 - 110,000

Full time

3 days ago

Be an early applicant

Get more replies from employers

Send a job-specific resume in minutes.

Job summary

Moody's Corporation seeks a senior Data/Analytics Engineer to design, build, and support scalable data, analytics, and AI solutions on the Databricks Lakehouse Platform in a large enterprise. You will design pipelines with Spark, SQL, Python, govern data products, collaborate with stakeholders, and advance automation, CI/CD, and governance while partnering with Salesforce, Power BI, Snowflake, Fabric.

This role emphasizes responsible AI, data quality, security, and scalability across Moody's

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 ETL/ELT pipelines for scalable analytics and AI use cases.
Knowledge of data modeling, governance, quality, and enterprise data architecture.
Experience integrating Salesforce, Power BI, Snowflake, Fabric.
Git, CI/CD, DevOps, automation frameworks.
Proficiency in AI concepts with hands-on AI tools; awareness of AI risk and ethical use.
Excellent communication and stakeholder management.

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, 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, troubleshoot, and enhance solution performance for reliability and scalability.