Cloud Data Engineer

Position Summary

We are seeking an experienced, highly skilled Cloud Data Engineer to support an Investment Operations & Fund Treasury Data Engineering team. The ideal candidate will have a strong background in cloud data engineering and architecture, preferably within asset management or financial services, and will be comfortable both assessing architectural approaches and remaining hands-on in the development and delivery of solutions across modern data technology platforms.

This role requires deep expertise in Snowflake, Azure, SQL, dbt, data warehousing, and cloud-native data pipelines, along with the ability to design scalable, reliable, and secure data solutions.

Key Responsibilities

• Design and implement scalable cloud data warehouse architectures, including 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 techniques where appropriate.
• Utilize modern cloud data frameworks to build modular, reusable SQL models across staging, intermediate, and mart layers with comprehensive documentation and lineage.
• Build and maintain scalable data pipelines that ingest data from diverse sources, including Snowflake shares, databases, APIs, event streams, and flat files.
• Implement batch and near-real-time ingestion patterns using cloud-native technologies, including incremental loads, CDC (Change Data Capture), and idempotent pipeline design.
• Optimize warehouse and query performance through materialization strategies, clustering keys, and platform-specific query tuning.
• Implement and maintain RBAC, column-level security, dynamic data masking, and row-level access policies to support least-privilege access and data privacy requirements.
• Establish and maintain CI/CD pipelines for warehouse deployments, including automated testing and promotion of transformation code across development, UAT, and production environments.
• Work within an Agile environment using JIRA, participating in sprint planning and delivering high-quality solutions on a consistent cadence.
• Apply AI-assisted development tools where appropriate to accelerate transformation development, data quality automation, and documentation workflows.
• Develop and maintain technical documentation, data models, pipeline runbooks, and data dictionaries.
• Support platform reliability through monitoring, troubleshooting, backfill/reprocessing strategies, operational alerting, and performance optimization.

Qualifications

• 10+ years of data engineering experience, with a demonstrated track record of hands-on development and end-to-end solution delivery.
• Proven experience designing scalable cloud data warehouse architectures, including layered architectures, schema design patterns, and physical data models.
• Deep hands-on expertise with Snowflake, including data modeling, performance tuning, cost-efficient design, and secure vendor data shares.
• Advanced SQL skills with strong knowledge of data warehousing concepts, including dimensional modeling, incremental processing, slowly changing dimensions, and semantic layers.
• Strong hands-on experience building cloud data solutions on Microsoft Azure, particularly Azure Data Factory (ADF) and Azure Data Lake Storage (ADLS).
• Hands-on experience with dbt, including modular model development across layered warehouse architectures.
• Familiarity with streaming and near-real-time ingestion technologies such as Azure Event Hubs and Kafka, including CDC and incremental processing patterns.
• Strong understanding of data platform reliability, including orchestration, backfill/reprocessing strategies, performance optimization, and operational support.
• Experience developing and maintaining data quality frameworks, operational alerting, and runbooks in SLA-driven environments.
• Experience implementing CI/CD pipelines for dbt and Snowflake, including Git-based workflows, automated testing, and environment promotion.
• Strong written and verbal communication skills with the ability to clearly document data models, pipelines, technical processes, and data definitions.
• Bachelor’s degree in Computer Science, Information Systems, or a related field.
• Experience within asset management, investment management, financial services, Investment Operations, or Fund Treasury is strongly preferred.