Senior Specialist - Data Management

Company:

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.