SAS Snowflake Data Engineer

About Company

Droisys is an innovation technology company focused on helping companies accelerate their digital initiatives from strategy and planning through execution. We leverage deep technical expertise, Agile methodologies, and data-driven intelligence to modernize systems of engagement and simplify human/tech interaction. Amazing things happen when we work in environments where everyone feels a true sense of belonging and when candidates have the requisite skills and opportunities to succeed. At Droisys, we invest in our talent and support career growth, and we are always on the lookout for amazing talent who can contribute to our growth by delivering top results for our clients. Join us to challenge yourself and accomplish work that matters 

 

Job Title            SAS Snowflake Data Engineer

Job Location    Atlanta, GA | Raleigh, NC | Richmond, VA (Onsite )

Duration           12 Months

Pay Rate            $55 TO $60/hr on C2C

 

Job description

 

Role Overview

 

The SAS Snowflake Lead will support SAS Remediation and Modernization program responsible for understanding legacy SAS logic re engineering business logic on Snowflake and building validated governed Gold layer data products aligned to domain driven architecture and regulatory requirements

 

This role is not a lift and shift SAS conversion role It requires strong business logic translation Snowflake centric engineering and strict validation discipline

 

Key Responsibilities

 

SAS Logic Understanding Translation
Analyze existing SAS programs macros data steps PROC SQL and batch workflows
Identify embedded business rules undocumented logic and dependencies on
SAS datasets
flat files
upstream systems
Resolve conflicts between SAS code mapping documents and business definitions in collaboration with SMEs
Classify SAS code by complexity criticality and reuse potential
 

Business Logic Re Engineering on Snowflake

 

Rebuild approved business logic using

Snowflake SQL
Snowpark Python where appropriate
Selective ETL tools Talend SAS Viya as per target design
Avoid direct SAS pattern replication apply set based cloud native designs
Ensure all future state logic consumes only Silver and Gold layers no direct SORSAS dependencies
 

Gold Layer Data Product Development

Design and implement domain oriented Gold layer data hubs eg Lending Deposits Operations Default Management
Consolidate common business logic across multiple SAS programs into reusable Gold entities
Build validated data products that functionally replicate legacy SAS outputs while enabling reuse
Align data models to enterprise taxonomies and domain definitions
 

Validation Testing Reconciliation

Develop and execute unit integration and reconciliation tests to validate Snowflake outputs against SAS baselines
Support parallel testing and output comparison where required for regulatory sign off
Analyze variances and work with SMEs to confirm acceptable thresholds
Produce audit ready validation artifacts
 

Governance CICD Production Readiness

Ensure compliance with SDLC CICD Git Path to Production P2P and Code Review Utility CRU requirements
Participate in deployment readiness hypercare and knowledge transfer
Support ongoing refinement of standards patterns and reusable components
 

Required Skills Experience

 

Core Technical Skills

Strong experience in Base SAS programming DATA steps PROC SQL macros
Proven experience migrating or modernizing SAS workloads
Strong hands on experience with Snowflake
SQL optimization
data modeling
performance tuning
Experience with Snowpark Python or Python based data engineering is a plus
Familiarity with ETL tools such as Talend SAS Viya selective usage
 

Data Engineering Architecture

Experience building domain driven data models and reusable data products
Strong understanding of Silver Gold layer separation
Ability to design scalable cost efficient Snowflake solutions
Understanding of data governance lineage and auditability requirements
 

Validation Quality

Experience in data reconciliation regression testing and data quality validation
Ability to work with large datasets and define meaningful validation metrics
Familiarity with automated testing approaches is a plus
 

Domain Soft Skills

Experience working with financial services banking data preferred
Strong analytical and problem solving skills
Ability to collaborate with business SMEs architects and governance teams
Clear documentation and communication skills
 

Droisys is an equal opportunity employer. We do not discriminate based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. Droisys believes in diversity, inclusion, and belonging, and we are committed to fostering a diverse work environment