Sr Operations Specialist, Operations

spgi; Greater London; On-site; GBP 60,000 - 90,000; Full time

Job summary

S&P Dow Jones Indices is seeking an ESG Data Owner within the Data Enablement team to govern ESG datasets used in equity and fixed income indices. You will manage data quality, documentation, lineage, controls, and issue resolution across data operations, technology, analytics, and vendor teams.

The role focuses on datasets such as GHG emissions, physical risk, ESG scores, and related sustainability data, ensuring completeness, accuracy, timeliness, and readiness for index operations and

Qualifications

• Bachelor’s degree in data science, finance, economics or math.
• 1–3 years of data analysis or ESG data experience.
• Foundational ESG frameworks and sustainability data knowledge.
• Basic finance and indexing concepts.
• Proficient in Python and SQL for data work.

Responsibilities

• Manage ESG datasets across the data lifecycle.
• Coordinate onboarding of new ESG data feeds and define data requirements.
• Design, run and improve data quality checks; resolve data issues.
• Document data sources, lineage, validation rules and controls.

Skills

Python

SQL

Data analysis

Data management

ESG data

Attention to detail

Education

Bachelor's degree in relevant field

Tools

Python

SQL

Job description

About the Role:

Grade Level (for internal use): 09 The Team:

The ESG Data Owner role sits within the Data Enablement team at S&P Dow Jones Indices. The team supports the management, validation, and delivery of datasets used in the maintenance and rebalance of S&P Dow Jones indices across multiple asset classes.

This role will focus on ESG data used in equity and fixed income indices, including datasets such as GHG emissions, physical risk, ESG scores, and related sustainability data. You will help ensure these datasets are accurate, well-documented, and ready for use by internal stakeholders.

You will work closely with technical, operational, and index teams to support reliable data delivery, improve data quality checks, and maintain clear data governance practices, including documentation, lineage, controls, and issue resolution.

Responsibilities and Impact

As an ESG Data Owner, you will play a central role in the day-to-day management, quality, and governance of ESG data used across S&P Dow Jones equity and fixed income indices. You will help ensure ESG datasets are complete, accurate, timely, and fit for use in index operations and analytics.

This role acts as a key point of coordination between data operations, technology, index management, analytics, and vendor teams. You will support the onboarding of new datasets, help define data requirements, monitor data quality, investigate issues, and contribute to improvements in ESG data processes and controls.

Key Responsibilities

• Manage ESG datasets across the data lifecycle, including ingestion, validation, quality review, documentation, and delivery for index use.
• Support the preparation and maintenance of ESG datasets such as GHG emissions, physical risk, ESG scores, and other sustainability-related data.
• Apply data standards, taxonomies, and governance controls to help maintain a consistent and trusted version of ESG data across index and analytics workflows.
• Design, run, and improve data quality checks to identify gaps, inconsistencies, outliers, and other data issues.
• Investigate and resolve data quality issues in collaboration with technology, operations, index management, and vendor teams.
• Help define data requirements for new or updated ESG data feeds, including field definitions, validation rules, lineage requirements, and operational handoff needs.
• Support the onboarding of new ESG datasets and help ensure they are integrated into existing systems and processes in a controlled and documented way.
• Maintain clear documentation of data sources, business rules, validation checks, known limitations, and data lineage.
• Act as a point of contact for internal ESG data questions, working with index managers and other teams to clarify data usage, resolve queries, and support methodology alignment.
• For complex data cases, prepare analysis and recommendations to support review by index managers, committees, or relevant internal stakeholders.
• Coordinate with ESG data vendors to clarify data definitions, delivery standards, issue resolution, and data changes.
• Stay informed on ESG market developments, data standards, and regulatory themes that may affect ESG data requirements.
• Prepare data analysis summaries, issue logs, and reporting materials to support internal reviews and stakeholder discussions.
• Support responses to client or stakeholder questions by providing accurate ESG data information through internal teams such as Client Services or Index Services.

What is in it for you?

• Opportunity to work in the financial data and index industry with a focus on ESG and sustainability data.
• Exposure to ESG datasets used across equity and fixed income indices.
• Opportunity to work with data management, index, analytics, sustainability, technology, and operations teams.
• Development of practical skills in data quality, data governance, validation, documentation, and pipeline support.
• Access to data management tools, analytical methods, and cross-asset index concepts.

What We’re Looking For:

Basic Required Qualifications:

• Bachelor's degree in Data Science, Finance, Economics, Mathematics, or a related field.
• 1-3 years of professional experience in data analysis, data management, ESG data, sustainability, indexing, or a similar financial or data-driven field.
• A foundational understanding of ESG frameworks, ratings methodologies, and sustainability data (e.g., GHG emissions, physical risk, ESG scores) and their application in financial indices.
• A foundational understanding of financial markets (equity & fixed income) and indexing concepts.
• Strong analytical and quantitative skills with the ability to work with large data sets.
• Proficiency in Python and SQL for data analysis, manipulation, and visualization with a willingness to further develop these skills in a financial data environment.
• Good written and verbal communication skills with the ability to explain complex topics clearly.
• Strong attention to detail and ability to manage multiple priorities and deadlines in a