Senior Cloud Data Engineer

Senior Consultant, Data Engineering About Our Firm: Granite Solutions Groupe provides financial services decision makers with people and solutions that deliver. Our clients count on us to deliver the right talent at the right time to achieve critical business results. We leverage our industry knowledge and passion for client priorities to deliver human capital solutions. GSG was founded in 1998 as a consulting firm delivering project management and technology solutions for the financial services industry. GSG now has a global presence, with team members deployed across the U.S. at Fortune 1000 companies and high-performing Fintech firms. High-caliber consultants are the face of GSG at our client organizations and offices. We value the deep relationships we have with our consultants that enable us to place them in roles where their skills will have an immediate impact. The GSG consulting team is comprised of diverse, experienced, driven, and dynamic contributors who excel at getting things done. About the Opportunity: GSG is seeking an experienced, highly skilled cloud data engineer to provide services to our client’s Investment Operations & Fund Treasury Data Engineering team. The ideal resource will have experience in asset management, technical and comfortable assessing Architectural approaches and is hands-on to work on solutions across various data technology platforms. Responsibilities: Design and implement scalable cloud data warehouse architectures, defining layer structures, schema design patterns, and partitioning/clustering strategies. Architect physical and logical data models that balance query performance, storage efficiency, and business domain clarity, applying dimensional modeling and data techniques where appropriate. Adopt cloud data frameworks to build modular, reusable SQL models across staging, intermediate, and mart layers with full documentation and lineage. Build and maintain data pipelines that ingest data from diverse sources, snowflake shares, databases, APIs, event streams, and flat files into the cloud data warehouse reliably and at scale. Implement batch and near-real-time ingestion patterns using cloud-native tools, managing incremental loads, CDC (change data capture), and idempotent pipeline design. Optimize query performance through materialization strategies, clustering keys, and warehouse-specific query tuning techniques. Implement and maintain role-based access control (RBAC), column-level security, dynamic data masking, and row-level access policies to enforce least-privilege and data privacy requirements. Establish and maintain CI/CD pipelines for warehouse deployments automating testing, and promotion of transformation code across dev, UAT, and production environments. Operate within an Agile environment using JIRA to manage work items, participate in sprint planning, and deliver high?quality solutions on a consistent cadence. Apply AI-assisted development tools pragmatically across the engineering lifecycle, accelerating warehouse transformation authoring, data quality automation, and documentation workflows. Requirements: Bachelor's degree in computer science, information systems, or a related field. 10+ years of data engineering experience, with a proven track record of hands?on development and end?to?end solution delivery. Proven ability to design scalable cloud data warehouse architectures, defining layered structures, schema design patterns and physical data models that balance query performance, storage efficiency, and business domain clarity. Deep expertise in Snowflake, including data modeling, performance tuning, and cost?efficient design, along with experience managing vendor data shares for secure and governed access. Advanced SQL skills with a strong foundation in data warehousing concepts, including dimensional modeling, incremental processing, slowly changing dimensions, and semantic layers. Hands-on experience designing and operating cloud data solutions on Azure including ADF, ADLS Storage, with a strong grasp of cloud-native ingestion patterns and pipeline orchestration. Proficiency in modern data transformation frameworks (dbt) including modular model design across layered warehouse architecture. Familiarity with streaming and near-real-time ingestion patterns (e.g., Azure Event Hubs, Kafka) including incremental load design, CDC, and latency-aware pipeline considerations. Strong understanding of platform reliability engineering for data warehouse covering orchestration, backfill and reprocessing strategies, and warehouse performance optimization. Experience designing and maintaining data quality frameworks with operational alerting and runbooks to support SLA-driven reliability. Experience implementing CI/CD pipelines for dbt and Snowflake workloads, including Git-based workflows, automated testing, and environment promotions. Strong written and verbal communication skills with the ability to produce clear data model documentation, pipeline runbooks, and data dictionaries. Experience in asset management, financial services, or investment-related, preferred. Employee Benefits: Comprehensive medical, dental, vision and prescription coverage. Company-paid life insurance. Eligible commuter benefits-like paying for work-related public transit and parking with pre-tax dollars. Pre-tax contributions that go directly into your 401K. Pet insurance, discount card and prescriptions. GSG’s Commitment to Diversity: As a diverse-owned business, GSG is committed to creating a diverse workforce, and we are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. #J-18808-Ljbffr