Marsh
Manager-DataEngineering
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Manager - Data Engineering at Marsh. Skills: Databricks, Python, PySpark, SQL. Design and implement scalable data pipelines. Implement AI Based solution using Databricks”
What You'll Achieve.
ensure data is transformed and optimized for analytical use; transforming raw data into meaningful insights; transforming raw data into AI Analytics; ensure data is accessible for business intelligence and analytics
Industry & Context.
troubleshoot data pipelines
returning to work after a break of 1 year or more
What They're Looking For.
Must Have
Develop and maintain data pipelines using Databricks, Design AI Based Solution using Databricks Genie, Expose/consume Databricks features via API, Write data transformation scripts using Python, Store and manage real time data in AWS S3, Use SQL to query, clean, and manipulate large datasets, Collaborate with cross-functional teams, Monitor and troubleshoot data pipelines, Document data processes, Ingest and process structured and unstructured data
Nice to Have
Databricks components like: Pipeline, scheduled / event based job, Genie, Unity Catalog and Datawarehouse, Proficiency in Python, PySpark, and SQL, Data Governance, Data access security, Configuring Job compute for different Jobs in Databricks, Version control using Git, Databricks API and its integration, Bulk data and real time data streaming understanding, Delta Lake and other Databricks technologies, Additional AWS services (e. g. , Athena, Glue, Lambda, S3, DMS )
What You'll Do.
Design and implement scalable data pipelines
Implement AI Based solution using Databricks
Handle end-to-end ETL/ELT processes
Manage large datasets
Transform raw data into meaningful insights
Transform raw data into AI Analytics
Collaborate with architects
Collaborate with business stakeholders
Develop and maintain data pipelines
Design AI Based Solution
Expose/consume Databricks features via API
Write data transformation scripts
Store and manage real time data
Integrate with other cloud-based services
and manipulate datasets
Collaborate with cross-functional teams
Monitor and troubleshoot data pipelines
Document data processes
Ingest and process structured data
Ingest and process unstructured data
How You'll Work.
Team & Collaboration
Collaborating closely with architects; Collaborating with business stakeholders; Collaborate with cross-functional teams
Full Job Description
## Company: Marsh Risk ## ## Description: "**“Restart Your Career with Us!** If you’re a skilled professional returning to work after a break of 1 year or more we invite you to apply and bring your valuable experience and fresh perspective to our team. Our Restart initiative is dedicated to supporting returnees with an inclusive, diverse environment where you can rebuild your career, contribute to exciting projects, and grow with us Apply now and be part of a culture that values your growth, well-being, and meaningful impact. Your comeback starts here with Marsh!” We are seeking a talented individual to join our Mercer Team at Marsh. This role will be based in Noida/Gurgaon/Mumbai/Pune . This is a hybrid role that has a requirement of working at least three days a week in the office. **Manager -** **Data Engineering** **We will count on you to:** As a Data Engineer, you will be responsible for designing and implementing scalable data pipelines and AI Based solution using Databricks. You will handle end-to-end ETL/ELT processes, manage large datasets, and work with tools like Python, PySpark, and AWS S3 to ensure data is transformed and optimized for analytical use. You’ll work on cutting-edge cloud and hybrid data projects, transforming raw data into meaningful insights and AI Analytics. You’ll be hands-on from day one, collaborating closely with architects and business stakeholders. **What you need to have:** * Develop and maintain data pipelines using Databricks and the Medallion Architecture (Bronze, Silver, Gold layers). * Design AI Based Solution using Databricks Genie and E2E integration. * Knowledge of exposing/consuming Databricks features via API using cloud-native tools or other application. * Write data transformation scripts using Python and PySpark. * Store and manage real time data in AWS S3 and integrate with other cloud-based services. * Use SQL to query, clean, and manipulate large datasets. * Collaborate with cross-functional teams to ensure data i
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