Job Title: Data Operation Engineer I
Company: McKinsey & Company
Location: Gurugram, Haryana, India
Description:
Who You'll Work With

Secure Foundation Cloud Services is an entity within McKinsey's global IT organization that provides IT support services to McKinsey firm members and clients.

The team is responsible for managing the firm’s global IT infrastructure and applications. Secure Foundation Cloud Services provides “Data Operation” services for McKinsey’s business operations. This group is responsible for operating and managing data products across multiple internal and external engagements, ensuring availability, reliability, and uninterrupted data delivery for the business.

It is a team of skilled engineers supporting our software developers, data analysts and data scientists, with initiatives to ensure optimal data delivery and consistency during engagements.

Beyond technology skills, our data operations engineers bring skills essential for client service, including problem solving, critical thinking, process orientation and business savvy. Team members are currently distributed globally across three time zones, IST, CET & EDT.

Your Impact

In this role, you will manage data pipelines and refreshes to ensure seamless data processing and availability.

You will investigate and fix data pipeline failures by conducting root cause analysis and applying necessary remediations.

Additionally, you will optimize and maintain data pipelines to support data integration and transformation.

You will build processes that support data ingestion, data transformation, qualitative analysis, and dependencies.

By working closely with data provider teams, you will resolve pipeline issues impacting data freshness and accuracy. When data feeder teams are unable to resolve discrepancies, you will raise and implement data fixes, ensuring data integrity in reporting layers.

You will lead the evaluation, implementation, and deployment of tools and processes to improve the way we work.

Identifying opportunities for process improvement, you will automate repetitive tasks and enhance existing data pipelines for long-term sustainability. Ensuring compliance with data governance and security policies will be a key responsibility.

Collaboration with other functions, such as data translators, data scientists, and data visualization engineers, will enable distinctive client service. Additionally, you will manage and support infrastructure platform configurations, resources, and provisioning for data services.

Your Qualifications and Skills


3+ years of experience with strong expertise to manage data products & pipelines (data ingestion & transformation) on cloud data platforms
Experience in identifying inefficiencies in data pipelines and implementing sustainable automation solutions
Strong proficiency in writing complex SQL queries for data validation, troubleshooting pipeline failures, and performing root cause analysis
Experience in scripting (Python) for automation, enhancing data pipelines, and optimizing operational workflows
Ability to handle data issues, collaborate with data feeder teams, and raise fixes for unresolved discrepancies
Experience with tools like Apache Airflow, AWS Glue, DBT, or other ETL frameworks for managing data workflows
Understanding of cloud databases (Snowflake, AWS RDS, Aurora, or SQL Server) and database recovery models
Have working knowledge of CI/CD tools such as GitHub Actions, JFrog, SonarQube etc.
Have experience in working on any one of the public cloud platforms (AWS/AZURE)
Have knowledge of visualization tools such as Tableau & Power BI etc.
Strong ability to work with cross-functional teams, including Data Engineers, Business Intelligence teams, and Infrastructure teams, ensuring timely issue resolution and process improvements
Proactive mindset to drive enhancements in data operations, optimize processes, and improve reliability through automation
Excited to work with data driven solutions and business problem solving
Ability to deal with ambiguity and rapid changes during different phases of solution development and delivery
Having any certification in the field of data engineering & analytics would be an added advantage
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