Data Engineering - Data, Lakehouse And AI Data Platform Engineer - Analyst - Dallas (AI)

TL;DR

Data Engineering - Data, Lakehouse and AI Data Platform Engineer (AI/Spark): Designing and maintaining large-scale data foundations and production pipelines for AI and analytics capabilities with an accent on reliability, governance, and high performance. Focus on building robust data assets, optimizing distributed data processing, and extending platform tooling for AI use cases.

Location: Dallas, Texas, United States (Onsite)

Company

Global investment banking and financial services firm known for integrating high-scale engineering at the center of its business operations.

What you will do

• Build, enhance, and support batch and streaming data pipelines on the Lakehouse and AI data platform.
• Develop raw, refined, and curated datasets that support analytics, reporting, and AI use cases.
• Implement controls to validate completeness, accuracy, and consistency of data across pipelines.
• Refactor and modernize existing data flows to improve reliability, performance, and maintainability.
• Collaborate with platform teams and data consumers to deliver scalable, production-ready data products.
• Contribute to shared tooling and framework components to improve platform operations and delivery.

Requirements

• Bachelor’s or master’s degree in a quantitative discipline or equivalent practical experience.
• Strong hands-on programming experience in Python or Java.
• Good working knowledge of SQL, including troubleshooting and optimization.
• Experience working with distributed data processing frameworks such as Apache Spark.
• Familiarity with software engineering fundamentals, version control, and CI/CD practices.
• Working knowledge of data formats including JSON, Avro, and Parquet.

Nice to have

• Experience with Snowflake, Apache Iceberg, Databricks, or the Hadoop ecosystem.
• Stronger ownership of technical design across multiple datasets or pipeline domains.
• Ability to lead delivery for a workstream and manage dependencies.
• Experience guiding implementation standards and engineering practices within a team.

Culture & Benefits

• Opportunity to work with a modern and evolving data stack including Snowflake and Databricks.
• Environment focused on solving complex technical problems and turning data into action.
• Strong emphasis on delivery-focused engineering and long-term professional growth.
• Collaborative team culture with a high standard for data correctness and testing.