Architecture & Design

Define and own the end-to-end Snowflake data architecture, including data modelling, storage, and compute strategies

Design scalable ELT/ETL frameworks for ingesting data from internal systems, third-party providers, and client sources

Establish best practices for performance optimization, cost control, and security

Implementation & Delivery

Lead hands-on development of Snowflake solutions, including schemas, pipelines, and data transformations

Build and optimize data ingestion pipelines (batch and real-time where applicable)

Integrate Snowflake with upstream and downstream systems (APIs, data lakes, reporting tools, etc.)

Data Integration & Financial Data Expertise

Design robust ingestion and normalization of financial datasets (positions, transactions, market data, pricing, reference data)

Ensure data consistency and lineage across portfolio management workflows

Governance & Security

Implement data governance frameworks including access control, auditing, and data quality monitoring

Ensure compliance with financial data regulations and client data security requirements

Leadership & Collaboration

Act as technical lead across the project lifecycle, mentoring engineers and guiding best practices

Collaborate with product managers, architects, and client teams to translate business requirements into technical solutions

Influence tooling and technology decisions across the data platform

Snowflake Expertise

Deep, hands-on experience with Snowflake architecture, performance tuning, and cost optimization

Strong understanding of Snowflake features (e.g., Snowpipe, Streams & Tasks, data sharing, zero-copy cloning)

Data Engineering

Proven experience designing and building enterprise-scale data warehouses

Strong SQL skills and experience with modern ELT tools (e.g., dbt, Airflow, or similar)

Experience with cloud platforms (AWS, Azure, or GCP)

Integration & Pipelines

Experience building robust data pipelines and integrating with APIs, message queues, and file-based ingestion

Familiarity with semi-structured data (JSON, Parquet, Avro)

Software Engineering Mindset

Strong understanding of CI/CD, testing, version control, and infrastructure-as-code

Ability to balance architectural thinking with hands-on delivery

Financial Services Domain (Highly Preferred)

Experience with asset management data models (portfolios, holdings, trades, valuations)

Understanding of market data vendors and financial data workflows

Nice to Have

Experience with data cataloging and governance tools

Familiarity with real-time streaming technologies (e.g., Kafka)

Exposure to regulatory reporting or risk analytics platforms

Experience working in a SaaS or product-led environment