Middle–Senior Data Engineer with AI Experience

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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 Data Engineer with AI experience and a strong background in building scalable data solutions and enabling AI-driven capabilities. This role combines deep expertise in data engineering with practical experience in integrating and supporting AI technologies.

The estimated salary for this position is up to USD 150,000 per year.

The position requires onsite attendance three days per week at the client’s location in New York City (NY), Iselin (NJ), or Charlotte (NC).

Technology stack

Python, SQL, NoSQL, Snowflake, Airflow, LLM/RAG, Flask, Streamlit, Azure/AWS/GCP.

Responsibilities

Design and develop scalable ETL and ELT data pipelines
Build and maintain data orchestration workflows using Apache Airflow or similar tools
Collaborate with AI engineers to integrate LLMs into data‑driven applications
Develop RAG pipelines using embeddings and vector‑based search
Optimize Snowflake data models for performance and cost efficiency
Contribute to cloud native application design and deployment
Support integration or development of MCP servers where applicable
Collaborate closely with product, data, and platform teams

Requirements

Mid‑level candidates with 4+ years and Senior candidates with 10+ years of professional experience in software or data engineering.
Strong experience building production-grade data pipelines
Experience with Snowflake
Hands-on experience with Apache Airflow or similar orchestration tools
Solid experience with Snowflake, including data modeling and performance tuning
Advanced SQL skills and working knowledge of NoSQL databases
Strong Python development experience
Experience working in cloud environments Azure, AWS or GCP

Nice to have

Hands on experience with large language models
Experience with retrieval augmented generation patterns
Experience with embeddings and vector databases
Experience using Streamlit or similar tools for GenAI interfaces
Exposure to MCP server development or integration

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