About the role

Senior Software Engineer building scalable data platforms and analytics solutions at S&P Global. Collaborating with teams to enable data-driven decision making and implementing cloud technologies.

Responsibilities

Design, develop, and maintain scalable data pipelines and data platforms across cloud environments using AWS and Google Cloud managed services.
Build and optimize ETL/ELT workflows using AWS Glue, AWS Step Functions, Amazon MWAA (Managed Workflows for Apache Airflow), and Google Cloud Data Fusion.
Work with large-scale structured and semi-structured data using formats such as Google Protocol Buffers and Apache Parquet (via cloud-managed engines/services that support Parquet storage/processing).
Develop and manage cloud analytics and warehouse/lakehouse solutions leveraging Databricks on AWS/GCP, Google BigQuery, and Microsoft Fabric.
Implement efficient data storage and retrieval solutions using managed databases such as Amazon DynamoDB, Amazon Aurora, Amazon RDS for SQL Server, Google Cloud SQL, and Azure SQL (as applicable).
Collaborate with product, data, and business stakeholders to enable analytics, reporting, and data-driven decision-making.
Create and maintain dashboards and visualizations using Microsoft Power BI, Tableau, and Amazon QuickSight.
Ensure data quality, governance, lineage, and observability using platform-native and enterprise tooling such as Databricks Unity Catalog, AWS CloudWatch, Google Cloud Operations Suite, and Microsoft Purview.
Write high-quality, maintainable code using Python and SQL/T-SQL, applying software engineering best practices (testing, code reviews, design patterns, performance tuning).

6-10 yrs strong experience with Databricks (e.g., workspaces, SQL Warehouses, governance capabilities such as Unity Catalog, and production-grade job orchestration).
Hands-on experience with AWS services such as Amazon S3, Amazon EC2, Amazon EMR, AWS Lambda, Amazon Athena, AWS Glue, and AWS Step Functions.
Experience with Google Cloud services including BigQuery, Cloud Storage, Compute Engine, Pub/Sub, Dataflow, and Cloud Data Fusion.
Proficiency in Python and SQL/T-SQL for data processing, transformation, and automation.
Strong knowledge of cloud-managed relational and NoSQL databases such as Amazon DynamoDB, Amazon Aurora, Amazon RDS for SQL Server, and Google Cloud SQL.
Familiarity with modern BI and analytics tools including Power BI, Tableau, and/or Amazon QuickSight.
Experience with modern data interchange/serialization formats such as Google Protocol Buffers and columnar storage formats such as Parquet commonly used in cloud analytics platforms.
Strong experience with GitHub for version control and engineering workflows.
Experience with Terraform for infrastructure provisioning and environment management.
Experience designing secure, scalable systems with strong operational rigor (SLAs/SLOs, monitoring, incident response, cost optimization).

Health & Wellness: Health care coverage designed for the mind and body.
Flexible Downtime: Generous time off helps keep you energized for your time on.
Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.
Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.