Job Description
Over the last 20 years, Ares’ success has been driven by our people and our culture. Today, our team is guided by our core values – Collaborative, Responsible, Entrepreneurial, Self-Aware, Trustworthy – and our purpose to be a catalyst for shared prosperity and a better future. Through our recruitment, career development and employee-focused programming, we are committed to fostering a welcoming and inclusive work environment where high-performance talent of diverse backgrounds, experiences, and perspectives can build careers within this exciting and growing industry. Job Description Position Overview We are seeking an exceptional Principal, Data Platforms to establish and lead our data engineering function from the ground up. This role reports to the Head of Data Engineering and is responsible for the complete design, development, and implementation of a world-class modern data platform. You will drive the strategic evolution of our data infrastructure, enabling both structured and unstructured data workflows at scale. You will spearhead the upgrade and modernization of our existing Azure Data Factory pipelines to next-generation orchestration tools, implement efficient data ingress and egress patterns, establish AI/LLM-native data capabilities through advanced vector indexing and streaming architectures, and build a strong data engineering organization from the ground up. You will collaborate closely with cloud engineering, network engineering, and data products teams to architect a unified data lake and comprehensive data governance framework that supports diverse analytical and operational needs across our portfolio. Key Responsibilities Organization Building & Team Leadership Build and scale the data engineering organization from inception, defining team structure, roles, and responsibilities across the function Establish engineering culture emphasizing technical excellence, collaboration, ownership, and continuous learning Recruit, mentor, and develop high-performing data engineers with expertise in modern data platforms, ETL/ELT, orchestration, streaming, and vector databases Partner with Human Resources on recruitment strategy, hiring processes, and organizational scaling as the firm grows Strategic Vision & Roadmap Establish a comprehensive, multi-year data engineering strategy aligned with firm objectives Define technical roadmaps for data infrastructure, platform capabilities, and technology adoption Establish governance frameworks for data engineering decisions, standards, and best practices Lead technology evaluation and vendor selection processes with clear ROI and strategic fit Platform Architecture & Modernization Design and architect a modern, scalable data platform leveraging Databricks on Azure that supports both structured and unstructured data at petabyte scale Lead the modernization of legacy Azure Data Factory (ADF) pipelines to production-grade orchestration platforms such as Prefect, or Apache Airflow Develop a comprehensive upgrade and migration roadmap for ETL/ELT pipelines, ensuring zero data loss, minimal downtime, and improved observability Lead the implementation of serverless and Zero ETL patterns to eliminate infrastructure management overhead and reduce time-to-insight Own cost optimization initiatives across the data platform, balancing performance, reliability, and operational efficiency ETL/ELT & Orchestration Excellence Build deep expertise in Directed Acyclic Graph (DAG) principles and modern workflow orchestration patterns for reliable, scalable pipeline management Evaluate, select, and implement best-in-class orchestration tools (Prefect, Airflow) that provide superior visibility, error handling, and data lineage tracking Establish patterns for dynamic DAG generation, conditional execution, and advanced error recovery strategies Design and enforce data quality frameworks within orchestration tools to catch issues at the pipeline level Create monitoring, alerting, and observability solutions for 100%+ visibility into pipeline health and data freshness Data Movement & Integration Patterns Architect efficient data ingress patterns supporting high-volume, real-time, and batch data inflows from diverse sources (APIs, databases, cloud services, SaaS platforms) Design sophisticated data egress patterns enabling secure, efficient data distribution to downstream systems, analytics tools, and external stakeholders Implement change data capture (CDC) patterns and incremental processing strategies to optimize resource usage and reduce latency Establish