Senior Specialist - Data Management

Marsh; Mumbai; Hybrid; INR 1,500,000 - 2,800,000; Full time

Job summary

Marsh is seeking a Senior Specialist - Data Management in Mumbai to design, build, and maintain high-performance data pipelines on the Databricks lakehouse platform. This hybrid role requires at least two days in the office per week and focuses on data transformations, data quality, and lineage across ingestion, transformation, and consumption layers.

You will mentor junior engineers, establish standards for DBT, CI/CD, and GitHub workflows, and collaborate with IT and business teams to deliver

Qualifications

• Bachelor's degree or equivalent professional experience in computer science / information systems / engineering.
• At least 4 years of hands-on data engineering / pipeline development experience.
• Proven track record designing and maintaining production data pipelines at scale.

Responsibilities

• Design, build, and maintain production data pipelines in Databricks across lakehouse architecture.
• Write optimized SQL and Python for data transformations with high performance.
• Develop and enforce DBT workflows with version control and documentation.
• Implement CI/CD pipelines for data pipeline code using GitHub Actions or similar.
• Mentor and guide team members on best practices and maintain coding standards.

Skills

SQL

Python

Databricks

DBT

GitHub

CI/CD

Cloud AWS

ETL/ELT

Data Modeling

Education

Bachelor's degree in Computer Science, Information Systems, Engineering

Tools

Databricks

DBT

GitHub

Spark

Airflow

Job description

Job Description:

Role - Senior Specialist - Data Management

No of roles - 1

Location - Mumbai

Last date to apply - 29th September 2026

We are seeking an experienced Data Engineer to join the Marsh Innovation and Data Office (IDO) - Data Strategy team in Mumbai. This hybrid role requires at least two days per week in the office and focuses on designing, building, and maintaining high-performance data pipelines across our Databricks analytics platform.

IDO Data Strategy is a global team of data engineering professionals working to deliver scalable, reliable data pipelines that power business decision-making across Marsh globally. The group has a footprint within the India Knowledge Services (IKS) function at Marsh Global Capability Centre in Mumbai, India. IKS is a hub of several hundred professionals that work with Marsh businesses across a wide range of capabilities.

What We Count On You To Do

Pipeline Design & Development (Primary Focus – 60%)

• Design, build, and maintain production data pipelines in Databricks that transform raw data from ingestion workspace through transformation workspace and into consumption workspace following a lakehouse architecture.
• Write clean, optimized SQL and Python code to implement efficient data transformations, ensuring high performance and maintainability across all three workspaces.
• Develop and enforce DBT (Data Build Tool) workflows for reproducible, version-controlled data transformations; define and manage data models, tests, and documentation.
• Implement CI/CD pipelines using GitHub Actions (or similar) to automate testing, validation, and deployment of data pipeline code across development, staging, and production environments.
• Manage code repositories using GitHub, including pull request workflows, code review standards, branch strategies, and version control best practices.
• Create comprehensive data mappings, transformation logic, and business rules documentation to ensure reliability and transparency of data lineage across ingestion, transformation, and consumption layers.
• Validate data quality and correctness through automated testing frameworks; reconcile datasets and troubleshoot pipeline failures in production environments.

Mentoring & Technical Leadership (Secondary Focus – 40%)

• Mentor and train team members on Databricks best practices, Python and SQL optimization techniques, DBT development patterns, and GitHub workflows.
• Establish and document coding standards, pipeline architecture patterns, and deployment best practices to promote consistency and quality across the data engineering team.
• Provide guidance on scalability, performance, and maintainability.
• Conduct code reviews for pull requests, ensuring adherence to standards and providing constructive feedback to elevate team capability.
• Foster a culture of continuous improvement by sharing lessons learned, emerging technologies, and industry best practices relevant to Databricks and data engineering.

Data Quality & Cross-Workspace Integration (Balanced – Supporting Responsibilities)

• Champion data quality and integrity across all three workspaces by defining quality metrics, rules, and monitoring processes.
• Collaborate with IT and business teams to ensure seamless data integration between source systems, Databricks platform, and downstream reporting systems.
• Identify and resolve data anomalies, validate transformations against business logic, and maintain SLAs for pipeline freshness and accuracy.
• Participate in requirements discussions with business stakeholders to translate high-level data needs into technical pipeline specifications (10-20% of time).
• Support system improvements by analyzing pipeline performance, identifying bottlenecks, and recommending optimizations to enhance data delivery.

What You Need To Have

• Minimum 12 months experience as Senior Specialist (C2)
• Should have at least “On-Track” or equivalent rating in last appraisal.
• Should not be under any Performance Counselling Plan or had any official disciplinary action within the last 3 months.
• Should not have applied for any other IJP in the last 3 months.

Education & Experience

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (or equivalent professional experience)
• At least 4 years of hands-on experience in data engineering, data pipeline development, or related roles
• Demonstrated experience designing and maintaining production data pipelines at scale

Technical Skills (Essential)

• Advanced proficiency in SQL – writing complex queries, window functions, CTEs, query optimization, and performance tuning
• Strong Python programming skills – writing production-quality, well-tested code for data transformation and orchestration
• Hands-on experience with Databricks – workspace configuration, lakehouse design, Delta Lake, Spark SQL, and cluster management
• Experience with DBT (Data Build Tool) – data modeling, macro development, testing frameworks, and documentation
• Proficiency with GitHub for version control – branching strategies, pull requests, merge workflows, and collaborative development
• Solid understanding of CI/CD concepts and experience deploying pipelines through automated testing and release pipelines
• Working knowledge of cloud platforms (preferably AWS: S3, EC2, Lambda, CloudFormation, or similar IaC tools)
• Familiarity with ETL/ELT design patterns and data architecture concepts (data warehousing, data lakes, lakehouse)

Technical Skills (Advantageous)

• Experience with orchestration tools such as Apache Airflow, Prefect, or Databricks Workflows
• Proficiency in additional programming languages (Scala, R) or tools (Spark, Kafka)
• Experience with data quality frameworks (Great Expectations, dbt tests, custom validation logic)
• Knowledge of containerization and infrastructure-as-code (Docker, Terraform)
• Experience with RDBMS systems (Oracle, SQL Server, Teradata) and data integration patterns

Professional Competencies

• Strong problem-solving and debugging skills with the ability to troubleshoot complex data pipeline issues
• Excellent communication skills – ability to explain technical concepts clearly to both engineers and non-technical stakeholders
• Self-directed learner with willingness to stay current with emerging technologies and data engineering best practices
• Ability to work independently on assigned pipeline development while also collaborating effectively within a team environment
• Familiarity with Agile methodologies (Scrum, Kanban) and tools such as Jira or Azure DevOps

Disclaimer:-

• Please note that the relocation assistance shall not be provided for the said position
• Candidates who wish to apply for inter-location positions are required to check with the Transport Help Desk (THD) to confirm if their place of residence is within the served transport service zone
• Mention your employee id and official email address in the resume

What Makes You Stand Out

• Demonstrated track record mentoring junior engineers and building high-performing data engineering teams
• Experience working with Informatica suite of tools or other enterprise data integration platforms
• Familiarity with commercial insurance business domain and insurance industry data structures
• Understanding of data governance principles and experience implementing data ownership and stewardship models
• Certifications such as Databricks Lakehouse Engineer, AWS Certified Data Analytics, or equivalent
• Prior experience establishing data engineering standards and best practices across an organization
• Strong track record delivering complex pipeline projects on time and to quality standards

Why Join Our Team

• Work with cutting-edge data engineering technologies (Databricks, DBT, cloud platforms) on real-world business problems
• Develop deep expertise across a modern analytics technology stack
• Mentor and grow the next generation of data engineers
• Professional development opportunities, interesting technical challenges, and supportive leadership
• Vibrant and inclusive culture where you can collaborate with talented colleagues to create innovative data solutions
• Access to a wide range of career opportunities across a global organization
• Competitive benefits and rewards to enhance your well-being.

Marsh (NYSE: MRSH) is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit marsh.com, or follow us on LinkedIn and X.

Marsh is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law.

Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor” day per week on which their full team will be together in person.