Job Title: Maestro Data Architect
Location: Stamford, CT – Onsite (Local or Willing to Relocate)
Duration: 12+ Months
Experience Required: 6–8 Years
Role Overview
We are seeking a Maestro Data Architect with strong expertise in Snowflake, data engineering, and cloud based data platforms. The role focuses on designing and building scalable ETL and ELT pipelines, optimizing data models, and ensuring high quality data processing across enterprise systems.
The ideal candidate will have hands on experience with Snowflake, strong SQL skills, and the ability to design efficient data architectures while collaborating with business and technical stakeholders.
Key Responsibilities
Design, develop, and maintain ETL and ELT pipelines using Snowflake, SQL, Python, and cloud platforms.
Build and optimize data models including staging, data warehouse, and data marts.
Implement performance tuning techniques such as micro partitioning and clustering.
Develop data ingestion pipelines for structured and semi structured data sources including JSON, Parquet, XML, and APIs.
Utilize Snowflake features such as Streams, Tasks, Time Travel, Zero Copy Cloning, and Snowpipe for automated data processing.
Collaborate with data architects, analysts, and business stakeholders to translate requirements into scalable solutions.
Monitor and troubleshoot data pipelines to ensure reliability and data integrity.
Document data flows, transformations, and technical processes for maintainability.
Implement job scheduling and orchestration using industry standard tools.
Required Skills and Qualifications
Education
Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related field is preferred.
Experience
6–8 years of experience in data engineering or data architecture roles.
Experience working with cloud based data platforms and data warehousing solutions.
Technical Skills
Strong hands on experience with Snowflake.
Strong SQL and PL SQL skills.
Experience building ETL and ELT pipelines.
Experience with Python for data processing and automation.
Knowledge of AWS cloud services.
Experience with data modeling and data warehousing concepts.
Experience with orchestration and scheduling tools such as Tidal or similar.
Experience handling structured and semi structured data formats.
Soft Skills
Strong analytical and problem solving abilities.
Excellent communication and stakeholder collaboration skills.
Ability to work independently and manage multiple priorities.
Strong documentation and organizational skills.
Preferred Qualifications
Basic understanding of banking or financial domain terminology.
Experience working in enterprise data platforms and analytics environments.
Familiarity with functional testing and data validation processes.
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