Snowflake Data Engineer

Logisoft Technologies Inc
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Remote

Tech stack

Airflow
Amazon Web Services (AWS)
Data analysis
Azure
Cloud Engineering
Information Engineering
ETL
Relational Databases
Python
Microsoft SQL Server
Oracle Applications
Performance Tuning
Power BI
SQL Databases
Tableau
Talend
Data Processing
Google Cloud Platform
Snowflake
Spark
Information Technology
Performance Monitor
Data Management
Data Pipelines

Job description

We are seeking a highly experienced Senior Snowflake Data Engineer with a strong background in modern cloud data platforms as well as legacy RDBMS and ETL systems., Design, develop, and optimize scalable data pipelines and data models in Snowflake Migrate and modernize legacy RDBMS/ETL systems into cloud-native architectures Build robust ETL/ELT pipelines using tools such as Informatics, Talend, dbt, or similar Work closely with business stakeholders, analysts, and portfolio teams to translate financial data requirements into technical solutions Ensure high data quality, integrity, and governance across multiple data sources Optimize Snowflake performance, cost, and storage strategies Integrate data from diverse financial systems including portfolio accounting, risk, and market data platforms Support reporting, analytics, and downstream BI tools

Requirements

The ideal candidate will have prior experience working within hedge funds or fund-of-funds environments, with a deep understanding of financial data, performance reporting, and investment workflows., 7+ years of experience in data engineering Strong hands-on experience with Snowflake (architecture, performance tuning, security).

Deep expertise in SQL and data modeling Proven experience with legacy RDBMS systems (Oracle, SQL Server, etc.).

Strong background in ETL/ELT development and migration Prior experience in hedge fund or fund-of-funds environments (highly preferred).

Solid understanding of financial data domains (NAV, holdings, performance, risk metrics).

Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.

Nice to Have

Experience with dbt, Airflow, or similar orchestration tools Familiarity with Python or Spark for data processing.

Exposure to financial reporting tools and BI platforms (Tableau, Power BI, etc.) Understanding of regulatory and compliance data requirements in asset management.

Soft Skills.

Strong problem-solving and analytical thinking Ability to work independently in a fast-paced environment Excellent communication skills with both technical and non-technical stakeholders.

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