Senior Data Engineer
S&P Global (company site, opens in a new tab)6+ yrsHyderabadOn-siteDirect career pageEst. 22–34 LPA
Posted 2d ago
Reach people at S&P Global
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at S&P Global you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead the transition and optimization of data pipelines to an enterprise data platform using AWS services and Databricks lakehouse technologies.
- Apply AI-assisted engineering tools (e.g., Claude, GitHub CoPilot, LLMs) to accelerate and improve quality of data engineering workflows, including code generation, testing, troubleshooting, and documentation.
- Provide senior technical leadership by defining standards, best practices, reusable engineering assets, and collaborating with global teams to ensure secured, governed, and scalable data platform delivery.
Minimum Requirements
- 6-8+ years of experience in data engineering, cloud data architecture, or related engineering fields with senior individual contributor or technical lead roles.
- Strong hands-on experience with Databricks platforms and AWS cloud-native data engineering (Amazon S3, AWS Glue, Lambda, Lake Formation, Kinesis, IAM).
- Practical experience using AI-assisted engineering tools (Claude, GitHub CoPilot, LLMs) and understanding of prompt engineering for AI output quality.
- Work Experience Required: 6-8+ years; Notice Period: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in complex, enterprise-scale data platform migrations and lakehouse architectures with emphasis on operational reliability, security, and governance.
- Skilled at blending hands-on engineering with senior-level technical guidance and delivery enablement across distributed global teams.
- Comfortable applying AI-assisted development techniques responsibly in a regulated environment, with knowledge of data mastering concepts and financial data domains