Snowflake Engineer (US Citizens only)

InvestM Technology LLC; Boston (MA); On-site; USD 140,000 - 200,000; Full time

Job summary

InvestM Technology LLC seeks a senior data engineer to design and implement scalable cloud data warehouse architectures on Snowflake and Azure. You will model both physical and logical structures, build modular dbt-driven pipelines, and ensure secure data access with RBAC and masking.

The role emphasizes end-to-end delivery in an Agile environment. You will optimize performance, support near-real-time ingestion, and promote code through dev, UAT, and production, collaborating with

Qualifications

• 10+ years of data engineering experience with end-to-end delivery.
• Design scalable cloud data warehouses with layered architectures.
• Deep Snowflake expertise including data modeling and cost-aware design.
• Advanced SQL and dimensional modeling foundations.
• Experience with Azure data services and cloud-native ingestion patterns.
• Proficiency with dbt and modern data transformation frameworks.
• CI/CD for dbt and Snowflake workloads with Git workflows.

Responsibilities

• Design and implement scalable cloud data warehouse architectures and schemas.
• Architect physical and logical data models balancing performance and storage.
• Build modular SQL models across staging, intermediate, and mart layers with documentation.
• Create and maintain data pipelines from diverse sources into the cloud warehouse at scale.
• Implement batch and near-real-time ingestion with CDC and idempotent designs.
• Optimize query performance with materialization and tuning techniques.
• Enforce RBAC, dynamic masking, and row-level security for data privacy.
• Establish CI/CD pipelines for warehouse deployments and automate testing and promotions.
• Work in Agile sprints using JIRA; contribute to planning and delivery cadence.
• Leverage AI-assisted tools to accelerate warehouse transformation and data quality workflows.

Tools

Snowflake

Azure

dbt

ADF

ADLS Storage

Kafka

Event Hubs

Job description

Primary Responsibilities Include

• 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.

Qualifications

• 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.
• Bachelor's degree in computer science, information systems, or a related field.
• Experience in asset management, financial services, or investment-related, preferred.