Data Engineer | ELT/BI Lead (Snowflake & Matillion)

AppLab Systems, Inc

Princeton (NJ)

On-site

USD 150,000 - 190,000

Full time

2 days ago

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Job summary

AppLab Systems, Inc. is seeking a Data Engineer/BI/ELT Developer to lead enterprise-grade data platforms in Jersey City, NJ onsite. You will own end-to-end data pipelines, design scalable warehouses, and drive automation and CI/CD practices across the data lifecycle.

The role requires 10+ years in data engineering, strong SQL and Snowflake expertise, and experience with Matillion. You will collaborate with architects, API teams, QA, and business stakeholders to deliver reliable data solutions.

Qualifications

10+ years of experience in Data Engineering / BI / Data Platforms.
Strong hands-on experience with Matillion and Snowflake.
Strong SQL expertise and database design / data modeling.
Experience with large-scale ETL pipelines and data transformations.
Proven automation mindset and implementations.
Experience with cloud data platforms (Snowflake preferred).
Agile delivery experience.

Responsibilities

Lead end-to-end data engineering delivery including ingestion, transformation, and persistence layers.
Own technical decisions related to database architecture, schema design, and data modeling.
Review and guide development of complex SQL, transformations, and performance-optimized data pipelines.
Act as the primary technical escalation point for data-related issues.
Design and implement Matillion/Snowflake ETL pipelines for structured and semi-structured data.
Build reusable, metadata-driven transformation frameworks.
Optimize data loads, transformations, and Snowflake performance.
Ensure data quality, consistency, and reconciliation across pipelines.
Drive automation-first approach across ETL deployments, validation, and data checks.
Enable CI/CD pipelines for data platforms (Git, automated deployments, environment promotion).
Collaborate with DevOps to enforce coding standards and release controls.
Reduce manual intervention through robust automation and monitoring.
Design enterprise data warehouse schemas, fact and dimension models, conformed layers.
Partner with Data Architects to align logical and physical models.
Ensure scalability, extensibility, and performance of data structures.
Lead data engineering workstreams in Agile sprints.
Support backlog grooming and technical story readiness.
Collaborate with API teams and Salesforce/UI teams for data enablement.
QA collaboration for test data, automation, and validation strategy.
Enforce data engineering best practices and compliance with governance guidelines.
Identify risks, dependencies, and gaps; contribute to RAID plans.