Client: Our client is a leading global corporate and investment bank, providing a wide range of financial services to large corporates, financial institutions, and institutional investors across international markets.
Project overview: The project involves migrating production data pipelines from legacy environments into a modern, cloud‑native data platform. The new platform enables domain‑oriented data products, scalable analytics, and embedded governance, with AI‑based tools supporting data quality, anomaly detection, privacy, and compliance.

• Position overview: We are looking for a Middle–Senior Software Engineer / Data Engineer with a strong background in data platform engineering and migration delivery. We are specifically seeking candidates with experience in platform migration initiatives, the ability to take ownership of an existing design, and the capability to deliver independently with minimal supervision.
• The ideal candidate will combine strong implementation skills with the ability to contribute to technical design discussions and execute complex migration work across modern cloud data ecosystems.
• The estimated salary for this position is up to USD 150,000 per year.
• Preference will be given to candidates who can work in a hybrid model from NYC, Iselin (NJ), or Charlotte (NC), three days per week.

Technology stack: Python, SQL, NoSQL, Databricks, Snowflake, Apache Airflow, Flask, Streamlit, LLM/RAG, Azure (AWS/GCP exposure is a plus).

• Responsibilities: Design, develop, and enhance scalable ETL and ELT data pipelines
• Take ownership of existing platform designs and deliver migration work independently with minimal guidance
• Contribute to solution design and ensure high-quality implementation aligned with platform architecture
• Lead and execute the migration of data assets and workloads to a modern cloud-based platform built on Databricks
• Build and maintain orchestration workflows using Apache Airflow or similar tools
• Optimize Snowflake data models for performance, scalability, and cost efficiency
• Work closely with product, data, and platform teams to support migration goals and platform evolution
• Contribute to cloud-native application design and deployment
• Collaborate with AI engineers to integrate AI/LLM-enabled capabilities where applicable
• Support the integration or development of MCP servers where relevant

• Requirements: Senior candidates: 10+ years of professional experience in software engineering, data engineering, or data platform development
• Mid-level candidates: 4+ years of professional experience in software engineering, data engineering, or data platform development
• Strong experience building production-grade data pipelines
• Hands-on experience with Databricks, Snowflake, and Azure
• Experience working on platform migration or modernization initiatives
• Proven ability to work from an existing design and deliver independently with minimal supervision
• Solid experience with Snowflake, including data modeling and performance tuning
• Hands-on experience with Apache Airflow or similar orchestration tools
• Strong Python development skills
• Advanced SQL skills and working knowledge of NoSQL databases
• Experience working within modern cloud data platforms and distributed engineering teams
• Good understanding of scalable architecture patterns and data platform best practices

• Nice to have: Experience with medallion architecture or similar layered data platform models
• Exposure to platform migration initiatives or large-scale enterprise data transformation programs
• Hands-on experience with large language models (LLMs)
• Experience with retrieval-augmented generation (RAG) patterns
• Experience with embeddings and vector databases
• Experience using Streamlit or similar tools to build GenAI interfaces
• Exposure to MCP server development or integration