We are seeking a hands-on Technical Data Business Analyst to join our Digital Trading Analytics (dTA) team in a global Oil & Gas organisation. You will collaborate with data engineers, analytics teams, and business stakeholders to design, test, and deliver high-quality data solutions. The ideal candidate will have a solid foundation in data analysis, reconciliation, testing, and stakeholder management.
Responsibilities
- Define and document business and data requirements for analytics and reporting use cases.
- Perform data profiling, gap analysis, and data quality validation.
- Lead and support data migration activities, including mapping, validation, and reconciliation of large datasets.
- Work closely with engineering teams to test and validate data pipelines and transformations.
- Develop and execute test plans for data products (functional, regression, and UAT).
- Work with market data feeds and reference data to support trading analytics solutions.
- Translate business needs into data models, reporting logic, and dashboards.
- Engage with stakeholders from trading, analytics, and IT teams to ensure successful delivery.
- Participate in Agile ceremonies (sprint planning, backlog grooming, story refinement).
Required Skills & Experience
- 5+ years’ experience as a Data Analyst or Technical Business Analyst.
- Strong experience in data analysis, reconciliation, and data testing.
- Proficiency in SQL and at least one scripting language (Python preferred).
- Solid understanding of relational databases and data warehousing concepts.
- Experience with market data, trading data, or financial reference data.
- Exposure to data visualisation tools such as Power BI or Tableau.
- Knowledge of Agile delivery practices using tools like JIRA or Azure DevOps.
- Excellent communication and stakeholder management skills.
Nice to Have
- Experience in energy or financial trading environments.
- Familiarity with Databricks, Snowflake, or other cloud data platforms.
- Understanding of data governance, lineage, and metadata management.
- Exposure to data cataloguing tools or data quality frameworks.
Seniority level
Employment type
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Industries
- IT Services and IT Consulting