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.