Technology & Digital

Data Operation Engineer I

Job ID: 96240
  • Gurugram
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Do you want to work on complex and pressing challenges—the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you’ve come to the right place.

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 Growth

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 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
Please review the additional requirements regarding essential job functions of McKinsey colleagues.
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FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law.

FOR NON-U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. For additional details regarding our global EEO policy and diversity initiatives, please visit our McKinsey Careers and Diversity & Inclusion sites.

Job Skill Group - CSSA
Job Skill Code - STE - Cloud Infrastructure Engineer I
Function -
Industry -
Post to LinkedIn - Yes
Posted to LinkedIn Date - Tue Mar 18 00:00:00 GMT 2025
LinkedIn Posting City - Gurugram
LinkedIn Posting State/Province -
LinkedIn Posting Country - India
LinkedIn Job Title - Data Operation Engineer I
LinkedIn Function - Information Technology
LinkedIn Industry - Information Technology and Services
LinkedIn Seniority Level - Mid-Senior level