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Senior Cloud Data Engineer
EvolverSan Francisco, United Statesfull_timeVerifiedPosted 10 Aug 2026
💰 $175,000/yr($145,000/yr – $175,000/yr)
About the role
Evolver is seeking an experienced, highly skilled cloud data engineer to provide services to our 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.
Primary 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.
Basic Qualifications
- 10 years of data engineering experience, with a proven track record of hands‑on development and end‑to‑end solution delivery.
- 7 years of experience in Snowflake, including data modeling, performance tuning, and cost‑efficient design, along with experience managing vendor data shares for secure and governed access.
- 7 years of experience in SQL skills with a strong foundation in data warehousing concepts, including dimensional modeling, incremental processing, slowly changing dimensions, and semantic layers.
- 5 years of 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.
- 5 years of 3xperience implementing CI/CD pipelines for dbt and Snowflake workloads, including Git-based workflows, automated testing, and environment promotions.
- Bachelor's degree in computer science, information systems, or a related field.
Preferred Qualifications
- 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.
- 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.
- 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.
Evolver is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender ident
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