Lead Software Engineer, Data and Payments Data Platform

What you'll do

• Design, build, and maintain scalable data pipelines and ETL/ELT workflows using Spark, Airflow, Kafka, and Flink.
• Develop data platform components including cataloging, quality frameworks, and semantic layers with embedded governance standards.
• Implement data modeling strategies such as fact and dimensional models to support analytics and reporting.
• Drive the adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed.
• Translate business requirements from stakeholders into production-grade technical solutions.
• Write, review, and debug high-quality production code while ensuring security and operational stability.
• Identify opportunities to automate the remediation of recurring issues in software applications and systems.
• Lead evaluation sessions with vendors and internal teams to assess architectural designs and new technologies.

What we're looking for

• Formal training or certification on software engineering concepts and 5+ years of applied experience.
• 3+ years of professional experience focused on data engineering or data platform development.
• Advanced proficiency in Python, Java, and SQL.
• Hands-on experience with distributed data processing frameworks such as Apache Spark and Flink.
• Experience designing and operating data pipelines on Databricks using orchestration tools like Apache Airflow.
• Proficiency with cloud data services including AWS S3, Glue, Redshift, Athena, EMR, Lake Formation, or equivalent.
• Demonstrated experience leading the use of approved AI-assisted software development tools while ensuring security and quality standards.
• Exposure to LLMs, RAG architectures, vector databases, and Infrastructure as Code (Terraform) or containerized deployments (preferred).