Data Engineer

S&P Global; Hyderabad; On-site; INR 1,200,000 - 1,600,000; Full time

Job summary

S&P Global Hyderabad is seeking a Data Engineer to design and maintain data ingestion pipelines for Fig datasets and related services. You will work with global stakeholders to enable scalable data processing across platforms and products.

The role emphasizes cloud-based ETL, distributed processing, and strong collaboration with data architecture teams. Prior experience with data warehousing and analytics platforms is highly valued.

Qualifications

• 4+ years of professional software development experience.
• Strong data processing and cloud technology skills.
• Solid understanding of RESTful services and API design.

Responsibilities

• Build new data acquisition and transformation pipelines using cloud tech.
• Collaborate with architecture and data integration teams to align pipelines.

Skills

Data processing

Cloud platforms

REST APIs

Databases (SQL/NoSQL)

Data warehousing

ETL

CI/CD

DevOps

Agile

Python/Scala/Java

Education

Bachelors in CS or related

Tools

Github

Grafana

Job description

About the Role

Grade Level (for internal use): 09

The Team: The Market Intelligence Industry Data Solutions business line provides data technology and services supporting acquisition, ingestion, content management, mastering, and distribution to power our Financial Institution Group business and customer needs. We focus on platform scalability to support business operations by following a common data lifecycle that accelerates business value. Our team provides essential intelligence for the Financial Services, Real Estate, and Insurance industries.

The Impact: The Data Engineering team will be responsible for implementing and maintaining services and tools to support existing feed systems. This enables users to consume FIG datasets and makes FIG data available for broader consumption and processing within the company.

What's in it for you: Opportunity to work with global stakeholders and engage with the latest tools and technologies.

Responsibilities

• Build new data acquisition and transformation pipelines using advanced data processing and cloud technologies.
• Collaborate with the broader technology team, including information architecture and data integration teams, to align pipelines with strategic initiatives.

What We’re Looking For

• Proficient in programming languages commonly used for data processing, Data orchestration and workflow management systems, Distributed data processing framework, relational database management systems and Big data processing frameworks
• Experience with large-scale data processing platforms.
• Deep understanding of RESTful services, good API design, and object-oriented programming principles.
• Proficiency in object-oriented or functional scripting languages.
• Good working knowledge of relational and NoSQL databases.
• Experience in maintaining and developing software in production environments utilizing cloud-based tools.
• Strong collaboration and teamwork skills, along with excellent written and verbal communication abilities.
• Self-starter and motivated individual with the ability to thrive in a fast‑paced software development environment.
• Agile experience is highly desirable.
• Experience with data warehousing and analytics platforms will be a significant advantage.
• Bachelor's degree in computer science or a related field, with at least 4+ years of professional software development experience.

Technical Expertise

• Data Engineering Expertise: Strong experience in distributed data processing and optimization using modern frameworks.
• Cloud Platforms: Proficient in leveraging cloud services for scalable data solutions, including ETL orchestration, containerized deployments, and data storage.
• Workflow Orchestration: Skilled in designing and managing complex data pipelines and workflows.
• Programming & Scripting: Proficient in writing clean, modular, and testable code for data processing tasks.
• Database Management: Solid understanding of both relational and non‑relational databases, including data querying and modelling.
• ETL & Data Architecture: Proven ability to design and implement robust ETL pipelines and optimise data models for performance and scalability.

Soft Skills

• Excellent communication skills - able to articulate technical concepts to non‑technical stakeholders.
• Strong interpersonal skills - collaborative, empathetic, and team‑oriented.
• Demonstrated ability to work on challenging projects and go the extra mile to deliver results.

Preferred Qualifications

• Experience with CI/CD pipelines, Github and DevOps practices is must.
• Familiarity with data lake and data warehouse architectures.
• Exposure to real‑time data processing frameworks, and observability tools like Grafana is added advantage.

Our Mission

Advancing Essential Intelligence.

Our People

We’re more than 35,000 strong worldwide-so we’re able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding new ways to measure sustainability to analysing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. Join us and help create the critical insights that truly make a difference.

Our Values

Integrity, Discovery, Partnership

Throughout our history, the world’s leading organisations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals.

Benefits

We take care of you, so you can take care of business. We care about our people. Tha