Data Engineering Manager

Manager - Data Engineering

Company:Oliver Wyman Description:

We are seeking a talented individual to join our Oliver Wyman team at Marsh McLennan. This role will be based in Pune/Gurgaon. This is a hybrid role that has a requirement of working at least three days a week in the office.

Manager – Data Engineering

The OWG Technology department is seeking a highly skilled and motivated Senior Data Engineer to play a critical role in our data transformation program. In this position, you will lead major projects and workstreams, collaborating closely with stakeholders to ensure the successful implementation of data solutions. You will also mentor and coach junior team members, providing guidance during sprints as a technical lead. Your expertise in cloud data platforms, particularly the Databricks Lakehouse, will be essential in driving innovation and best practices within the team.

We will count on you to:

• Lead the design and implementation of processes to ingest data from various sources into the Databricks Lakehouse platform, ensuring alignment with architectural and engineering standards.
• Oversee the development, maintenance, and optimization of data models and ETL pipelines that support the Medallion Architecture (Bronze, Silver, Gold layers) to enhance data processing efficiency and facilitate data transformation.
• Utilize Databricks to integrate, consolidate, and cleanse data, ensuring accuracy and readiness for analysis, while leveraging Delta Lake for versioned data management.
• Implement and manage Unity Catalog for centralized data governance, ensuring proper data access, security, and compliance with organizational policies and regulations.
• Collaborate with business analysts, data scientists, and stakeholders to understand their data requirements and deliver tailored solutions that leverage the capabilities of the Databricks Lakehouse platform.
• Promote available data and analytics capabilities to business stakeholders, educating them on how to effectively leverage these tools and the Medallion Architecture for their analytical needs.
• Lead the migration of existing ETL processes from Informatica IICS and SSIS to cloud-based data pipelines within the Databricks environment, ensuring minimal disruption and maximum efficiency.
• Act as a technical lead during sprints, providing guidance and support to team members, and ensuring adherence to best practices in data engineering.
• Engage with clients and stakeholders to support architectural designs, address technical queries, and provide strategic guidance on utilizing the Databricks Lakehouse platform effectively.
• Stay updated on industry trends and emerging technologies in data engineering, particularly those related to Databricks, cloud data solutions, and ETL migration strategies, continuously enhancing your skills and knowledge.
• Demonstrate excellent problem-solving skills, with an ability to see and solve issues before they affect business productivity.
• Demonstrate thought leadership by contributing to the development of best practices, standards, and documentation for data engineering processes within the organization.

What you need to have:

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
• Minimum of 7+ years of experience in data engineering or a related data role, with a proven track record of leading projects and initiatives.
• Expertise in designing and implementing production-grade Spark-based solutions.
• Expertise in query tuning, performance tuning, troubleshooting, and debugging Spark or other big data solutions.
• Proficient in big data technologies such as Spark/Delta, Hadoop, NoSQL, MPP, and OLAP.
• Proficient in cloud architecture, systems, and principles, particularly in AWS.
• Proficient in programming languages such as Python, R, Scala, or Java.
• Expertise in scaling ETL pipelines for performance and cost-effectiveness.
• Experience in building and scaling streaming data pipelines.
• Strong understanding of DevOps tools and best practices for data engineering, including CI/CD, unit and integration testing, automation, and orchestration.
• Cloud or Databricks certification is highly desirable.

What makes you stand out:

• Excellent verbal and written communication skills, comfortable interfacing with business users
• Good troubleshooting and technical skills
• Able to work independently

Why join our team:

• We help you be your best through professional development opportunities, interesting work and supportive leaders.
• We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities.
• Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.

Marsh McLennan (NYSE: MMC) is a global leader in risk, strategy and people, advising clients in 130 countries across four businesses: Marsh, Guy Carpenter, Mercer and Oliver Wyman. With annual revenue of $24 billion and more than 90,000 colleagues, Marsh McLennan helps build the confidence to thrive through the power of perspective. For more information, visit , or follow on LinkedIn and X.Marsh McLennan 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 McLennan 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 McLennan 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. Experience LevelSenior Level

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