Sr. Data Analyst, Compliance

Jobgether; Brasil; Remote; BRL 220,000 - 360,000; Full time

Benefits offered by this job

Remote work from Brazil

Professional development

Cross-functional collaboration

Impact on compliance and risk

Opportunity to work with ML projects

Job summary

Jobgether is seeking a Senior Data Analyst, Compliance based in Brazil. You will build data pipelines and production-grade detection logic to enhance transaction monitoring and risk management in a fast-paced fintech environment.

You will collaborate with cross-functional teams, translate regulatory requirements into actionable analytics, and develop dashboards for leadership visibility. A strong statistical background and English proficiency are required.

Qualifications

• At least 7 years in data analytics, data science, or data management in fintech/finance or related fast-paced industries.
• Experience collaborating with compliance, fraud, funding, finance, or customer support teams.
• Proficiency in Python and SQL with production-grade data systems experience.
• Experience with dbt or similar data modeling tools.
• Experience building and managing data pipelines and workflow orchestration.
• Familiarity with CI/CD, version control, testing, and production maintenance.
• Strong statistical background with feature engineering and hypothesis testing.
• Proficiency in BI tools and executive dashboards.
• Ability to investigate production issues, communicate findings, and present recommendations.
• Education in analytics, software engineering, statistics, economics, or related field.
• Fluency in English; residence in Brazil, Canada, or the United States.

Responsibilities

• Own and refine transaction monitoring rules with compliance stakeholders.
• Translate regulatory requirements into reliable detection logic for alerting and thresholds.
• Develop and maintain Python and SQL pipelines for data preparation and detection workflows.
• Evaluate detection performance by coverage, alert quality, and threshold sensitivity.
• Design reproducible evaluations using historical data with imperfect labels.
• Manage testing, deployment, and monitoring of detection workflows and data quality issues.
• Backfill historical data with validation and traceability for reliable alerts.
• Analyze large datasets to identify trends and provide actionable business insights.
• Build and maintain dashboards for visibility into compliance performance.
• Apply software engineering practices across pipelines and dashboards and explore ML opportunities.

Skills

Python

SQL

Data modeling

Pipeline orchestration

Statistical analysis

Problem solving

Communication

Data visualization

Education

Bachelor's degree in analytics, CS, statistics, or related field

Tools

dbt

Airflow

Athena

Trino

Kafka

Kubernetes

S3

Job description

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Sr. Data Analyst, Compliance based in Brazil.

As a Senior Data Analyst, Compliance, you will use advanced analytics and data engineering to strengthen compliance operations within a fast-paced, global financial technology environment. You will work at the intersection of data analytics, transaction monitoring, and risk management, helping teams identify emerging patterns, improve detection capabilities, and make informed decisions. From building reliable data pipelines to developing sophisticated monitoring rules, your work will directly contribute to operational efficiency and risk mitigation. You will collaborate closely with compliance and cross-functional stakeholders to turn complex requirements into actionable, measurable outcomes. This remote opportunity offers the chance to shape data-driven compliance strategies while contributing to innovative financial services and future machine learning initiatives.

Accountabilities

• Transaction Monitoring: Own and refine the logic and rules used to monitor deposits and withdrawals, collaborating with compliance stakeholders to identify transaction patterns and improve detection effectiveness.

• Detection Logic Development: Translate compliance requirements into reliable, production-ready detection logic, ensuring accuracy across alert eligibility, thresholds, customer segmentation, date windows, and duplicate handling.

• Data Pipeline Engineering: Develop and maintain Python and SQL pipelines for transaction data preparation, feature engineering, and detection workflows.

• Detection Performance Evaluation: Assess detection rules and analytical models based on coverage, alert quality, threshold sensitivity, and the potential impact of proposed changes.

• Historical Analysis and Testing: Design reproducible evaluations using historical data, accounting for limited labels, imbalanced datasets, and evolving customer behavior.

• Production Operations: Manage testing, deployment, scheduling, monitoring, and ongoing support for detection workflows, investigating data quality issues, pipeline failures, and unexpected results.

• Data Backfills and Integration: Execute historical data backfills with appropriate validation and traceability, ensuring reliable downstream alert delivery and integration with compliance systems.

• Analytics and Business Insights: Analyze large datasets, investigate root causes and emerging trends, and deliver actionable recommendations that improve business performance and operational efficiency.

• Reporting and Visualization: Build and maintain dashboards and analytical outputs that provide clear visibility into compliance performance and support data-informed decision-making.

• Continuous Improvement: Apply software engineering best practices across pipelines and dashboards while experimenting with new approaches, testing hypotheses, and contributing to future machine learning and intelligence capabilities.

Requirements

• Professional Experience: At least 7 years of experience in data analytics, data science, or data management, ideally within fintech, cryptocurrency, financial services, or the gambling industry in a fast-paced, high-growth environment.

• Cross-Functional Collaboration: Experience working with compliance, fraud, funding, finance, or customer support teams to solve practical business problems using data.

• Python and SQL: Strong proficiency in Python and SQL, with hands-on experience developing, maintaining, and supporting production-grade data or analytical systems.

• Data Modeling: Experience with dbt or similar tools for structuring, transforming, and maintaining reliable datasets for reporting and decision-making.

• Pipeline Orchestration: Experience building and managing data pipelines, with a solid understanding of workflow orchestration and dependable data processing practices.

• Software Engineering Practices: Familiarity with version control, automated testing, code reviews, continuous integration and deployment (CI/CD), and production system maintenance.

• Statistical Analysis: A strong statistical foundation and the ability to apply analytical methods, feature engineering, and hypothesis testing to complex business challenges.

• Business Intelligence: Proficiency with data visualization and business intelligence tools such as Hex, Tableau, Power BI, or equivalent platforms, including the development of executive-facing dashboards.

• Problem-Solving and Communication: Ability to investigate production issues independently, interpret complex findings, communicate uncertainty clearly, and present recommendations to non-technical stakeholders.

• Education: A degree in an analytically rigorous discipline, such as analytics, software engineering, statistics, economics, or a related field.

• Language and Location: Fluency in English and current residence in Brazil, Canada, or the United States.

• Additional Advantage — Risk Analytics: Experience in fraud detection, anti-money laundering (AML), anomaly detection, or other risk-related applications.

• Additional Advantage — Data Infrastructure: Familiarity with technologies such as Athena, Trino, Kafka, and Kubernetes, alongside tools such as Airflow, dbt, and S3.

• Additional Advantage — Detection Optimization: Experience analyzing transaction patterns, segmenting customers, tuning detection thresholds, and evaluating systems with sparse or delayed investigation feedback.

• Additional Advantage — Machine Learning: Experience developing or deploying machine learning models, including experiment tracking, performance monitoring, and model evaluation.

• Additional Advantage — Governance: Knowledge of explainability, auditability, and change control within regulated environments.

• Mindset: A strong interest in data-driven compliance, continuous improvement, and the evolving financial technology landscape.

Benefits

• Remote Work: The flexibility to work remotely from Brazil within an internationally distributed organization.

• Meaningful Impact: The opportunity to strengthen compliance and transaction monitoring capabilities in a technology-driven financial services environment.

• Technical Ownership: End-to-end responsibility for analytical systems, detection logic, data pipelines, and production workflows.

• Advanced Analytics: Opportunities to explore statistical methods, detection optimization, experimentation, and emerging machine learning applications.

• Cross-Functional Exposure: Collaboration with compliance, finance, fraud, and other business and technical teams.

• Professional Development: Opportunities to deepen expertise in data engineering, risk analytics, financial technology, and production-grade analytical systems.

• Inclusive Work Environment: A merit-based environment that values diverse backgrounds, perspectives, skills, and professional experiences.

• Skills-Based Assessment: Job-related assessments may be used as part of the recruitment process to evaluate relevant competencies alongside experience and interviews.