Senior Financial Business Intelligence Analyst
CRI-Sabana
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
What you’ll work on
Full postingProfile, reconcile and analyze reporting data to find anomalies and inconsistencies
Investigate and resolve reported data quality issues
Build data quality standards, processes and exception tolerance policies
Maintain data definitions, tools and documentation to map and correct data issues
Provide QA for data assets built for new internal reports
From the employer’s posting
comprehensive data profiling, reconciliation, and analysis to identify anomalies and inconsistencies in reporting data
Investigate, analyze, and resolve reported data quality issues
Develop and implement data quality standards and processes
Develop and maintain internal processes, tools, and documentation repositories to effectively map, prevent, and correct data quality issues
provide quality assurance (QA) for data assets created to support new internal reports
Education & alternatives
What experience you need: - Bachelor’s degree in Information Systems, Computer Science, Finance, or a related field (or equivalent practical experience) - 5+ years of experience wrangling, preparing, and transforming complex datasets
Tools in this posting
- Python
- SQL
- BigQuery
- Power BI
- Tableau
- NumPy
- pandas
- Google Cloud (GCP)
Source — Tool mentions in context
- 5+ years of experience wrangling, preparing, and transforming complex datasets - 4+ years of experience analyzing large, multidimensional datasets using advanced analytical tools (e.g., SQL, Python) - 4+ years of experience applying data governance principles and practices
- 3+ years of Financial Planning & Analysis (FP&A) experience - Hands-on proficiency with Python and core data science libraries (e.g., Pandas, NumPy) - Experience building and managing data pipelines using Google Cloud tools (e.g., Cloud Composer, Dataproc) or real-time data processing tools (e.g., Cloud Dataflow)
- 4+ years of experience using self-service data visualization tools (e.g., Tableau, Power BI) - 1–2 years of experience with BigQuery or equivalent cloud-based big data platforms What could set you apart:
- 4+ years of project management experience and a self-motivated approach - 4+ years of experience using self-service data visualization tools (e.g., Tableau, Power BI) - 1–2 years of experience with BigQuery or equivalent cloud-based big data platforms
- Hands-on proficiency with Python and core data science libraries (e.g., Pandas, NumPy) - Experience building and managing data pipelines using Google Cloud tools (e.g., Cloud Composer, Dataproc) or real-time data processing tools (e.g., Cloud Dataflow) - Proven experience working with large-scale datasets, regulatory reporting frameworks, or credit-decisioning workflows within a fintech or financial services environment
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 8, 2026 · 10 days ago
- Recorded sightings
- 35
- Last seen by us
- Oct 18, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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Job description
The Financial Business Intelligence (BI) Data Quality Analyst is responsible for ensuring that our data and reporting are accurate, complete, and consistent. Primary responsibilities include identifying data quality issues, developing processes to address them, monitoring data quality over time, and creating and maintaining data definitions and documentation. The Data Quality Analyst will also collaborate with data engineers and data scientists to provide quality assurance (QA) for data assets created to support new internal reports.
What you'll do:
- Develop and implement data quality standards and processes, including comprehensive data profiling, reconciliation, and analysis to identify anomalies and inconsistencies in reporting data
- Ensure the integrity of all data consumed or produced by the Finance BI team, and develop formal policies for exception tolerance
- Advocate for and lead proactive initiatives to drive data completeness and quality
- Investigate, analyze, and resolve reported data quality issues
- Develop and maintain internal processes, tools, and documentation repositories to effectively map, prevent, and correct data quality issues
- Analyze problems, identify root causes, formulate findings, and communicate recommended solutions to internal stakeholders
- Collaborate cross-functionally with business users, database developers, and data engineers to resolve data quality issues and implement continuous improvements
What experience you need:
- Bachelor’s degree in Information Systems, Computer Science, Finance, or a related field (or equivalent practical experience)
- 5+ years of experience wrangling, preparing, and transforming complex datasets
- 4+ years of experience analyzing large, multidimensional datasets using advanced analytical tools (e.g., SQL, Python)
- 4+ years of experience applying data governance principles and practices
- 4+ years of experience working within Agile frameworks and product development environments
- 5+ years of experience managing customer or stakeholder relationships, with exceptional communication skills
- 4+ years of project management experience and a self-motivated approach
- 4+ years of experience using self-service data visualization tools (e.g., Tableau, Power BI)
- 1–2 years of experience with BigQuery or equivalent cloud-based big data platforms
What could set you apart:
- Proven ability to work independently with strong attention to detail and a focus on execution
- 3+ years of Financial Planning & Analysis (FP&A) experience
- Hands-on proficiency with Python and core data science libraries (e.g., Pandas, NumPy)
- Experience building and managing data pipelines using Google Cloud tools (e.g., Cloud Composer, Dataproc) or real-time data processing tools (e.g., Cloud Dataflow)
- Proven experience working with large-scale datasets, regulatory reporting frameworks, or credit-decisioning workflows within a fintech or financial services environment
- Demonstrated history of using Large Language Models (LLMs) and AI tools to increase daily productivity, workflow efficiency, and deliverable quality
Primary Location:
CRI-SabanaFunction:
Function - FinanceSchedule:
Full timeSource details
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CRI-Sabana
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