About Truelogic At Truelogic we are a leading provider of nearshore staff augmentation services headquartered in New York. For over two decades, we’ve been delivering top-tier technology solutions to companies of all sizes, from innovative startups to industry leaders, helping them achieve their digital transformation goals. Our team of 600+ highly skilled tech professionals, based in Latin America, drives digital disruption by partnering with U.S. companies on their most impactful projects. Whether collaborating with Fortune 500 giants or scaling startups, we deliver results that make a difference. By applying for this position, you’re taking the first step in joining a dynamic team that values your expertise and aspirations. We aim to align your skills with opportunities that foster exceptional career growth and success while contributing to transformative projects that shape the future. Our Client operates in the financial services sector, providing residential mortgage solutions. The company originates, services, and invests in home loans, offering purchase, refinance, and servicing platforms. It leverages data, technology, and capital markets expertise to manage risk, optimize pricing, and support homeowners throughout the loan lifecycle. Job Summary Senior Data Platform Engineer specializing in enterprise-scale data warehousing and advanced Snowflake architectures. Leads the design, optimization, and governance of high-performance data platforms supporting mission-critical analytics and financial systems. Combines deep Snowflake expertise with strong software engineering foundations in Python, cloud infrastructure, and DataOps. Proven at performance tuning, cost optimization, secure data modeling, and CI/CD implementation. Adept at translating complex data architectures into actionable solutions through cross-functional, agile collaboration. Responsibilities Lead the design, architecture, and optimization of enterprise-scale Snowflake data warehouse environments. Manage advanced Snowflake features including multi-cluster warehouses, data sharing, streams, tasks, time travel, and zero-copy cloning. Drive performance tuning, query optimization, and cost management at an enterprise level. Design and implement robust data models and dimensional schemas using modern warehouse patterns. Develop scalable data pipelines using Python 3, applying OOP principles and design patterns. Orchestrate data workflows using tools such as Apache Airflow, Pandas, and SQLAlchemy. Design and expose RESTful APIs and event-driven integrations to enable cross-platform data flow. Implement cloud infrastructure using Infrastructure as Code on AWS with Terraform, CDK, or CloudFormation. Enforce data security through RBAC, data masking, and row-level security policies. Establish DataOps best practices, including CI/CD pipelines, automated testing, and monitoring. Qualifications and Job Requirements