Design and develop enterprise-grade data pipelines, ETL/ELT processes, and APIs
Build and optimize data infrastructure components that support real-time analytics, reporting, and AI/ML implementation into pipelines
Implement data quality monitoring, validation, and lineage tracking systems to ensure data integrity across the organization
Develop microservices and containerized applications (Docker, Kubernetes) for scalable data processing and integration
Write clean, well-documented, and testable code following enterprise standards and best practices
Participate in code reviews, performance optimization, and technical design discussions
Support CI/CD pipeline development and automation for data platform deployments
Troubleshoot production issues and implement solutions with minimal downtime

3+ years of experience and strong proficiency in one or more programming languages (Python, Spring, Java, Scala, Go)
Advanced SQL and experience with relational and NoSQL databases
Hands-on experience with cloud data platforms (AWS, Azure) or on-premises data warehouse solutions
Familiarity with analytical and cloud data lakehouse platforms (Databricks, Snowflake)
Understanding of data modeling, ETL patterns, and data governance principles
Experience with containerization, orchestration, and deployment technologies (Docker, Kubernetes, Terraform)
Knowledge of ML/AI workflows, model deployment, and inference pipelines
Proficiency with version control systems (Git) and CI/CD tools
Strong problem-solving skills and ability to work independently with minimum supervision
Excellent communication skills and ability to collaborate across technical and business teams
Nice to have: Experience with data mesh or decentralized data architecture patterns
Familiarity with streaming technologies (Kafka, Apache Flink)
Knowledge of data security, encryption, and compliance frameworks (GDPR, HIPAA)
Exposure to observability and monitoring tools (Grafana, Datadog, Prometheus, ELK stack)
Agile/Scrum development experience
Background in machine learning operations (MLOps) or data engineering best practices

A comprehensive Total Rewards Program including bonuses and flexible benefits
Competitive compensation
Commissions and stock where applicable
Leaders who support your development through coaching and managing opportunities
Ability to make a difference and lasting impact
Work in a dynamic, collaborative, progressive, and high-performing team
A world-class training program in financial services
Flexible work/life balance options
Opportunities to do challenging work

Software Developer

Key skills