Analytics Engineer

SUMMARY:
Analytics Engineer

POSITION INFO:

Role overview:

As an Analytics Engineer, you’ll bridge the gap between data engineering and analytics, designing robust data models and enabling scalable insights for business, product, risk, and compliance teams. This is a high-impact role for someone who thrives on technical precision, collaboration, and delivering trusted data assets that power strategic decisions.

This role ensures that our client’s financial and operational data is accurate, reliable, and analytics-ready. You will:

• Build analytics-ready data models that serve as the backbone for BI and advanced analytics
• Enable self-service analytics for stakeholders across the organization
• Drive data quality and governance for regulated financial metrics

Duties

• Design, build, and maintain fact and dimension tables using best-practice modelling technique
• Transform raw data into structured, analytics-ready datasets using modern frameworks (e.g., dbt
• Apply version control, testing, and deployment best practices for reliable data pipelines
• Ensure accuracy, consistency, and compliance for financial and operational metrics
• Define and maintain business KPIs, metric definitions, and semantic layers
• Document all data models, transformations, and assumptions for transparency
• Partner with data engineers to optimize pipelines and warehouse performance
• Support analysts and business teams with self-service dashboards and reporting
• Troubleshoot and resolve data issues impacting reporting, compliance, and performance
• Introduce modern data stack practices to improve scalability and efficiency
• Advocate for data literacy and best practices across analytics teams
• Contribute to data architecture decisions and roadmap planning

Requirements

• 3+years related experience
• Bachelor’s degree in Computer Science, Data Analytics, Engineering, Mathematics, or related field
• Strong SQL skills and experience with large datasets
• Hands-on experience with modern data warehouses (Snowflake, BigQuery, Redshift)
• Familiarity with data modelling concepts (star schema, dimensional modelling)
• Understanding of BI tools (Power BI, Tableau, Looker)
• Experience working in Agile, cross-functional environments
• Experience in FinTech, banking, or financial services
• Knowledge of financial metrics (revenue, churn, fraud, risk indicators)
• Experience with dbt, Airflow, or similar orchestration tools
• Familiarity with Python or scripting for automation
• Understanding of data governance and compliance (SOC2, GDPR)
• Ability to translate business requirements into technical solutions