Senior Data Engineer at Flex Finance

Job Summary

•  We are seeking a highly skilled Senior Data Engineer to join our engineering team and lead our data infrastructure's design, development, and maintenance. You will be pivotal in building pipelines that power real-time financial analytics, risk management, and AI-driven decision-making across our product suite.

Key Responsibilities

• Architect, build, and maintain scalable data pipelines and ETL processes from multiple data sources (transaction data, third-party APIs, internal services).
• Optimize and manage our data lake and warehouse (AWS, Redshift, or similar) to support analytics and product features.
• Partner with product, engineering, and finance teams to define data requirements and deliver accessible, clean, and reliable datasets.
• Implement best practices for data governance, security, compliance (especially PCI DSS), and access control.
• Monitor, debug, and improve the performance of our data infrastructure and tooling.
• Mentor junior data engineers and contribute to technical design reviews.
• Work closely with our AI/ML team to support experimentation, model training, and production inference with high-quality datasets.

Requirements

• 5+ years of experience in data engineering or backend engineering roles.
• Deep proficiency in Python, SQL, and distributed data processing (e.g., Apache Spark, Airflow).
• Hands-on experience with cloud data architecture (preferably AWS – Lambda, S3, Redshift, DynamoDB).
• Experience building real-time and batch data pipelines.
• Solid understanding of database systems (SQL and NoSQL), performance tuning, and data modeling.
• Experience working with financial or transactional data is a plus.
• Familiarity with compliance and regulatory requirements for data handling in fintech is a strong advantage.
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.

Nice to Have

• Experience with GraphQL or REST API data integrations.
• Exposure to business intelligence tools like Metabase, Looker, or Power BI.
• Familiarity with AI/ML pipelines or experimentation frameworks.
• Previous experience in a fast-paced startup or fintech environment.