Overview
On Site
Full Time
Skills
Data Modeling
AWS
Python
Data Engineering
data lake
data warehousing
snowflake
AWS Lambda
data governance
data mesh
AWS Glue
risk management
Financial services
Data Architecture
AWS S3
AWS EC2
Sigma/Power BI
Job Details
Role: Senior Data Architect
Location: NYC, NY / Jersey City, NJ (Onsite)
Job Type: Full Time
Required Skills:
Snowflake, AWS, Python, Sigma/Power BI
- This position description identifies the responsibilities and tasks typically associated with the performance of the position.
- Other relevant essential functions may be required.
Must Have:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
- 15+ years of experience in data architecture, data engineering, or a similar role, with a proven track record of designing and delivering large-scale data solutions.
- Extensive, hands-on experience with Snowflake, including performance tuning, security best practices, and cost management.
- Expert-level knowledge of the AWS ecosystem, including S3, EC2, Lambda, Glue, IAM, and networking fundamentals.
- Advanced programming proficiency in Python for data manipulation, pipeline development, and automation.
- Demonstrable experience architecting and delivering data solutions for BI and analytics, with direct experience using tools like Sigma and/or Power BI.
- Crucially, extensive experience and deep domain knowledge of financial services back-office operations, specifically within Risk Management (e.g., trade lifecycle, settlement risk, counterparty data, collateral).
- Expert-level understanding of data architecture patterns (e.g., Data Warehousing, Data Lake, Data Mesh), data modeling, and data governance principles.
- Must be based in or willing to relocate to the New York City metropolitan area.
Preferred Qualifications:
- Deep, practical experience with data security principles and implementation, including data encryption (at-rest, in-transit), tokenization, and managing Material Non-Public Information (MNPI).
- Experience with data transformation tools like dbt (Data Build Tool).
- Familiarity with infrastructure-as-code (IaC) tools such as Terraform or CloudFormation.
- Knowledge of streaming data technologies (e.g., Kafka, Kinesis).
- Strong understanding of financial instruments across equities, fixed income, and derivatives.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.