Data Platform Engineer (AI, Lakehouse)

TL;DR

Data Platform Engineer (AI/Lakehouse): Building and optimizing high-performance data pipelines and curated datasets for the firm's AI and analytics platform with an accent on data quality, reliability, and scalability. Focus on designing robust data models, implementing distributed processing solutions, and leading technical delivery within a complex financial engineering environment.

Location: Must be based in Dallas, TX, United States

Company

A leading global financial institution at the forefront of engineering scalable systems and data-driven solutions.

What you will do

• Design, build, and maintain batch and streaming data pipelines on a modern Lakehouse platform.
• Develop raw, refined, and curated datasets to support analytics, reporting, and AI initiatives.
• Implement data quality controls, reconciliation processes, and monitoring to ensure production reliability.
• Refactor and modernize existing data flows to improve performance and maintainability.
• Collaborate with platform teams and data consumers to deliver high-quality data products.
• Provide technical leadership, mentor junior engineers, and define implementation standards.

Requirements

• 7-12+ years of professional experience in data engineering or software development.
• Strong hands-on programming proficiency in Python or Java.
• Advanced SQL skills including troubleshooting and performance optimization.
• Experience with distributed data processing frameworks such as Apache Spark.
• Solid understanding of temporal data modeling, schema design, and data partitioning techniques.
• Familiarity with CI/CD practices, version control, and production release discipline.

Nice to have

• Experience with modern data stack technologies like Snowflake, Databricks, or Apache Iceberg.
• Knowledge of Kafka and containerized deployment approaches like Kubernetes.
• Experience working with common data formats including JSON, Avro, and Parquet.

Culture & Benefits

• Opportunity to work on high-impact, large-scale data systems at the center of the business.
• Exposure to a modern, evolving data stack and complex financial engineering challenges.
• Collaborative environment focused on technical excellence and pragmatic problem-solving.
• Clear pathways for long-term career growth and technical leadership within the firm.