Negotiable
Undetermined
Hybrid
London, England, United Kingdom
Summary: The Technical Data Business Analyst role focuses on supporting the Digital Trading Analytics portfolio within the Oil & Gas industry. The position requires a strong technical foundation in data analysis, management, and testing, particularly in trading and analytics platforms. The analyst will engage in data-driven initiatives, ensuring data quality and consistency while collaborating with various stakeholders. This role is hybrid, requiring three days a week in the office.
Key Responsibilities:
- Gather, define, and document business and data requirements for analytics and reporting projects.
- Conduct data profiling, gap analysis, and root cause investigation to ensure data quality and consistency.
- Lead data migration efforts, including mapping, validation, and reconciliation across platforms.
- Collaborate with data engineers to validate pipelines, transformations, and ingestion processes.
- Design and execute test plans, including functional, regression, and user acceptance testing (UAT).
- Work with market and reference data sources to support trading analytics.
- Translate complex business requirements into structured data models and reporting logic.
- Actively engage stakeholders from trading, analytics, and IT departments.
- Participate in Agile ceremonies such as sprint planning, story refinement, and backlog grooming.
Key Skills:
- 5+ years of experience as a data or business analyst in a trading or energy environment.
- Proficiency in SQL and Python for data querying and transformation.
- Solid background in data reconciliation, testing, and profiling.
- Experience with relational databases and data warehousing concepts.
- Exposure to market data and financial reference data.
- Knowledge of Agile frameworks and tools such as JIRA or Azure DevOps.
- Excellent communication skills and stakeholder engagement capabilities.
- Familiarity with data visualization tools (e.g., Power BI, Tableau) is a plus.
- Exposure to cloud platforms (e.g., Databricks, Snowflake) is a plus.
- Understanding of data governance, lineage, and metadata management is a plus.
- Experience with data cataloguing and quality frameworks is a plus.
Salary (Rate): undetermined
City: London
Country: United Kingdom
Working Arrangements: hybrid
IR35 Status: undetermined
Seniority Level: undetermined
Industry: Other
Job Title: Technical Data Business Analyst – Digital Trading Analytics
Location: London (Hybrid: 3 days/week in-office mandatory)
Contract Duration: 12 to 24 months (based on performance)
Industry Experience Required: Oil & Gas
Overview
We are seeking a skilled Technical Data Business Analyst to join the Digital Trading Analytics (dTA) portfolio. This position is ideal for candidates with a strong technical foundation in data analysis, management, and testing—especially within trading, market data, and analytics platforms. This role offers a unique opportunity to contribute to data-driven initiatives supporting trading and analytics use cases across the Oil & Gas domain.
Key Responsibilities
- Gather, define, and document business and data requirements for analytics and reporting projects.
- Conduct data profiling, gap analysis , and root cause investigation to ensure data quality and consistency.
- Lead data migration efforts, including mapping, validation, and reconciliation across platforms.
- Collaborate with data engineers to validate pipelines, transformations, and ingestion processes.
- Design and execute test plans, including functional, regression, and user acceptance testing (UAT) .
- Work with market and reference data sources to support trading analytics.
- Translate complex business requirements into structured data models and reporting logic.
- Actively engage stakeholders from trading, analytics, and IT departments.
- Participate in Agile ceremonies such as sprint planning, story refinement, and backlog grooming.
Required Skills & Experience
- 5+ years of experience as a data or business analyst in a trading or energy environment.
- Proficiency in SQL and Python for data querying and transformation.
- Solid background in data reconciliation, testing, and profiling .
- Experience with relational databases and data warehousing concepts.
- Exposure to market data and financial reference data .
- Knowledge of Agile frameworks and tools such as JIRA or Azure DevOps .
- Excellent Communication Skills And Stakeholder Engagement Capabilities.
Nice to Have
- Familiarity with data visualization tools (e.g., Power BI, Tableau).
- Exposure to cloud platforms (e.g., Databricks , Snowflake ).
- Understanding of data governance , lineage , and metadata management .
- Experience with data cataloguing and quality frameworks .