In this role, you will:

• Architect & build advanced analytics products that blend data engineering with AI/ML intelligence and LLM capabilities.
• Lead end-to-end: from identifying the business-critical challenge, to designing the solution, to deploying at scale in production.
• Break down complexity into clear, actionable components that accelerate delivery.
• Mentor and guide peers and junior engineers, shaping both technical direction and culture.
• Continuously improve reliability, scalability, and performance in a high-impact environment.
• Innovate hands-on with technologies like Python, Scala, Java, Apache Spark, AWS Cloud Services, Iceberg Data Lakehouse, Apache Druid (OLAP), Kafka, Airflow, and cutting-edge ML/LLM frameworks.
• Direct impact on the financial heartbeat of the company.
• Freedom to spot AI opportunities and bring them to life with production-grade solutions.
• A culture that values engineering creativity, not just execution.

Experience & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field—or equivalent professional experience.
• 4+ years of experience building scalable data pipelines and software solutions (ETL/ELT, batch, and real-time) in cloud environments.
• Proficiency in Apache Spark (Scala or PySpark), SQL, Python(Scala or JAVA), Kafka, Iceberg, and Airflow.
• Prior experience with AI/ML technologies and their practical application in analytics solutions.
• Strong communication skills, with the ability to explain technical concepts to both technical and non-technical audiences.
• Self-starter mindset with strong organizational skills, curiosity, and a team-oriented approach.
• Background in finance, analytics, or reporting preferred.