Senior Lead Data Engineer - R01561957

Brillio 2

Edison, New Jersey, United States Remote permanent

Posted: March 4, 2026

Required Skills

Job Description

About Brillio:

Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction.
Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year.

Lead Data Engineer

Primary Skills:
• ETL Fundamentals, SQL, SQL (Basic + Advanced), Python, Data Warehousing, Modern Data Platform Fundamentals, Data Modelling Fundamentals, PLSQL, T-SQL, Stored Procedures

Specialization:
• ETL Specialization: Data Engineer

Job requirements:
• Extensive ETL/ELT Experience in data engineering with expertise in ETL pipeline design, migration, and optimization across large-scale enterprise systems. • Snowflake & Cloud Data Warehousing – Hands-on experience in migrating workloads to Snowflake, optimizing performance with clustering/partitioning, and working with AWS, Azure, and GCP ecosystems. • SQL & Data Modeling – Strong SQL proficiency with experience in Snowflake and DB2, building optimized queries, transformations, and data warehouse models. • DataStage & SSIS Background – Migrated legacy ETL processes to IBM DataStage and has practical experience in SSIS (SQL Server Integration Services), aligning well with required tools. • SAS & Analytics Exposure – Worked with SAS scripts and statistical models in financial/AML environments, integrating them into Snowflake pipelines to support compliance and analytics needs.

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