Director Data & Systems Engineering

Overview

We are seeking a hands-on Director of Data & Systems Engineering to lead our Data Engineering and Software Engineering functions. This player-coach leader will own the architecture, delivery, and operational excellence of enterprise data platforms, APIs, backend systems, and business-critical applications supporting trading, risk management, asset management, analytics, and operations.

The ideal candidate combines strong technical leadership with deep expertise in modern data platforms, distributed systems, and cloud-native engineering. While not an AI-focused role, this leader will partner closely with AI teams to ensure platforms are optimized for AI-enabled use cases.

Key Responsibilities

• Lead and mentor a team of engineers across Data, Software, API, and Platform Engineering.

• Define technology strategy, architecture standards, and engineering best practices.

• Drive development and modernization of trading, asset management, and enterprise platforms.

• Own enterprise data strategy, including Snowflake architecture, data pipelines, governance, quality, and performance optimization.

• Oversee delivery of APIs, backend services, integrations, and internal applications.

• Partner with business stakeholders to translate requirements into scalable technology solutions.

• Ensure platform reliability, security, observability, CI/CD maturity, and operational excellence.

• Collaborate with AI teams to support RAG, semantic search, vector databases, model-facing APIs, and responsible AI initiatives.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field.

• 15+ years of experience in Software Engineering, Data Engineering, Platform Engineering, or Architecture.

• 7+ years of leadership experience managing engineering teams.

• Strong hands-on expertise in Python, Snowflake, Databricks, FastAPI, REST APIs, PostgreSQL, Redis, Azure, and distributed systems.

• Experience designing and operating large-scale data platforms, APIs, and cloud-native applications.

• Strong knowledge of DevOps, CI/CD, observability, testing, and production operations.

• Working knowledge of AI/LLM technologies, including RAG, embeddings, vector databases, and model integration.

• Excellent communication skills with the ability to engage technical and executive stakeholders.

Preferred

• Experience in energy trading, commodities, financial services, or other data-intensive industries.

• Exposure to Snowflake Cortex, Azure OpenAI, Azure AI Services, LangGraph, Semantic Kernel, MCP, or similar modern AI/data platforms.

Technology Stack: Python, Snowflake, Databricks, FastAPI, PostgreSQL, Redis, Azure, APIs, Distributed Systems, AI/LLM Platforms.