Grade Level (for internal use):
09
The Role: Platform Engineer
The Team: The team is responsible for building, maintaining, and evolving the data intelligence architecture, data pipelines, and visualizations. It collaborates with business partners and senior management, working within multi-functional agile teams to ensure data integrity, lineage, and security. The team values self-service, automation, and leveraging data to drive insights and improvements. The team also values professionalism, collaboration, and mutual respect fostering a culture where every member demonstrates strong teamwork and positive behavioral traits while leveraging AI and modern tools to deliver excellence.
The Impact: This role is pivotal in transforming raw data into actionable insights that improve productivity, reduce operational risks, and identify business opportunities. By designing and implementing robust data solutions and visualizations, the Data Intelligence Engineer directly supports data-driven decision-making across various levels of the organization. The position contributes to extracting tangible value from data assets, ultimately enhancing overall service performance and business outcomes.
Whats in it for you:
- Opportunity to design, build, and maintain a scalable, flexible, and robust data intelligence architecture leveraging Microsoft Fabric and modern data engineering tools..
- Engage in AI-driven analytics and creative data science using Python (Pandas, NumPy) to provide actionable insights that directly influence business productivity and risk reduction strategies.
- Work in a dynamic environment focused on self-service and automation, with opportunities to utilize and expand knowledge in cloud environments (AWS, Azure, GCP).
- Collaborate within multi-functional agile teams, contributing to data-driven development and enhancing your skills in a supportive setting.
- Utilize GitHub for version control, collaboration, and CI/CD integration within agile workflows.
Responsibilities:
- Build and maintain the data intelligence architecture, ensuring it is scalable, flexible, robust, and cost-conscious.
- Design, build, and maintain efficient Data Pipelines and Fabric-based datasets , focusing on loose coupling, data integrity, and lineage
- Develop Data Visualizations with a focus on data security, self-service capabilities, and intelligible temporal metrics to highlight risks and opportunities.
- Conduct data science and AI analysis with Python, Pandas, and NumPy to generate predictive and prescriptive insights.
- Work with business partners to identify how value can be extracted from data, emphasizing self-service and automation.
- Define, measure, and maintain key performance metrics, statistics for senior management, customer stats, business trend analysis, and overall service statistics.
- Maintain source code repositories, documentation, and CI/CD workflows through GitHub .
- Demonstrate strong teamwork, professionalism, and respectful communication , contributing to a positive and inclusive team culture.
What Were Looking For:
- Key Qualifications:
- Bachelors degree required, with an overall experience of 4-8 years, including 3-4 years in Data Intelligence and 2-3 years in Development & Support.
- Strong experience in Python (with hands-on expertise in Pandas and NumPy ) or other scripting languages (e.g., Shell, PowerShell).
- Strong SQL skills with experience in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, DynamoDB, Redshift).
- Minimum 3+ years experience in development/automation areas, including automating data ingestion, transformation, and aggregation, and working knowledge of cloud technologies like AWS, Azure, or GCP (including Blob/flat file processing).
- Experience with Power BI or Tableau, including designing dashboards with trending visuals. Good to have knowledge of DAX, Power BI service, dataset refreshes, and performance optimization tools.
- Experience with Microsoft Fabric and Power BI , including designing dashboards, semantic models, and dataflows.
- Experience using GitHub for version control, collaboration, and CI/CD automation.
- Soft Skills:
- Strong communication skills to effectively interact with both technical and non-technical teammates and stakeholders.
- Proven ability to work independently and collaborate effectively in multi-functional agile teams.
- Strong problem-solving and analytical skills with an understanding of agile software development processes and data-driven development.
- A thorough understanding of the software development life cycle and agile techniques is beneficial.
- Strong behavioral alignment with S&P Globals values demonstrating accountability, empathy, and a positive attitude in cross-functional teamwork.
