Data Engineer (Record to Report)

Summary

The R2R Data Engineer is a technical expert responsible for architecting and implementing enterprise-scale data infrastructure that powers critical financial analytics and reporting for A Finance. This role requires deep technical expertise in modern data engineering practices including building high-performance ETL/ELT pipelines designing scalable data models and implementing robust data quality frameworks that ensure accuracy and consistency across financial systems.

This position demands hands-on experience with cloud-native data platforms advanced SQL optimization and programmatic data transformations. The engineer will work cross-functionally with business users FDT IS&T data scientists and other engineers to develop production-grade data services that support financial close processes regulatory reporting and strategic decision-making.

You will be working in enterprise data warehouse (Snowflake) Dataiku and lakehouse environments (AWS S3) to design dimensional models implement data governance policies and optimize query performance for large-scale financial datasets.

Key Qualifications

Required Technical Skills:

• 5 years of advanced Python programming experience including object-oriented design asynchronous programming and package development
• Expert-level SQL skills including complex joins window functions CTEs query optimization and performance tuning in databases
• Hands-on experience designing and implementing data models in Snowflake including time-travel zero-copy cloning data sharing and cost optimization strategies
• Proven experience building production-grade ETL/ELT pipelines processing large volumes of data
• Strong experience with AWS services including S3 Lambda EC2 IAM Secrets Manager and CloudWatch
• Experience implementing data security controls including encryption at rest/in transit data masking tokenization and row-level security
• Hands-on experience with CI/CD pipelines using GitHub
• Strong Git version control skills including branching strategies pull requests and code review processes
• Proficiency in shell scripting (Bash) for automation and system administration tasks

Preferred Technical Skills:

• Experience with streaming data platforms (Kafka Kinesis Pub/Sub) and real-time data processing frameworks (Spark Streaming Flink)
• Knowledge of containerization (Docker) and orchestration platforms (Kubernetes ECS)
• Experience with data catalog and metadata management tools (Alation Collibra DataHub)
• Experience with data quality frameworks (Great Expectations Soda Monte Carlo)
• Experience building and consuming RESTful APIs using frameworks like FastAPI or Flask

Business & Soft Skills:

• Understanding of financial processes including Record-to-Report (R2R) Order-to-Cash (O2C) Procure-to-Pay (P2P) or financial planning
• Experience working with ERP systems (SAP Oracle Financials) and extracting data from these platforms
• Strong problem-solving skills with ability to debug complex data issues and performance bottlenecks
• Excellent communication skills with ability to explain technical concepts to non-technical stakeholders
• Experience working in Agile/Scrum environments with cross-functional teams

Education and Experience

• Bachelors degree in Computer Science Computer Engineering Data Engineering Mathematics Statistics or other quantitative discipline required
• 5 years of professional experience in data engineering roles with demonstrated expertise in building production data systems
• Masters degree in a related field preferred