We are seeking a Data Business Analyst with a hybrid skill set that bridges data engineering and business analysis. This role involves hands-on data analysis, metric design, and close collaboration with client-side stakeholders to ensure clarity and alignment on business intent particularly in areas where documentation is missing, outdated, or ambiguous.
This is a 12-month contract role to start with a potential to extend.
You will act as a key link between business teams and technical functions, ensuring data solutions and reporting outputs are both technically robust and aligned with business objectives.
Key Responsibilities:
- Collaborate with business stakeholders to elicit, clarify, and validate the intent and expected behavior of key business metrics.
- Investigate existing data models and systems to understand current logic and identify discrepancies or undocumented logic.
- Work with engineering teams to define metric calculations, data transformations, and reporting logic.
- Translate business needs into clear technical data requirements, stories, or documentation.
- Ensure alignment between business expectations and data products, especially in cases with missing or ambiguous documentation.
- Conduct root cause analysis when metrics behave unexpectedly or inconsistently.
- Support the validation and QA of data pipelines, dashboards, and reports.
- Facilitate discussions across both business and technical teams to resolve data ambiguity.
Required Skills & Experience:
- 8+ years experience in a data analyst, business analyst, or analytics engineer role.
- Strong SQL skills and a solid understanding of data modeling and ETL/ELT processes.
- Experience working closely with both business users and engineering teams.
- Proven ability to investigate and reverse-engineer metric definitions.
- Excellent communication and stakeholder management skills.
- Strong analytical thinking and problem-solving abilities.
Preferred Qualifications:
- Familiarity with BI and visualization tools (e.g., Tableau, Power BI, Looker).
- Experience working with modern data stacks (e.g., Snowflake, dbt, BigQuery, Dataform).
- Understanding of agile methodologies and working in sprint-based environments.
- Prior experience in financial services, technology, or regulated industries is a plus.
Argyll Scott Consulting Pte Ltd
