Data Engineer/BI / ELT Developer || Only W2 Consultants || Remote work

AppLab Systems, Inc; Princeton (NJ); On-site; USD 150,000 - 190,000; Full time

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.

Skills

10+ years data eng

Matillion/Snowflake

SQL & data modeling

ETL pipelines

Automation mindset

Cloud data platforms

Agile delivery

Tools

Matillion

Snowflake

Job description

Title:

Data Engineer/BI / ELT Developer

Location:

Jersey City, NJ || Onsite Role

Mode:

Contract || Long Term

Job Summary

The BI / ELT Developers will be responsible for leading the design, development, and delivery of enterprisegrade data solutions with a strong focus on automation, ETL orchestration (Matillion), database design (Snowflake), and data transformations. This role will provide technical leadership across the data engineering lifecycle and partner closely with architects, API teams, QA, and business stakeholders to enable scalable and reliable data platforms.

Key Responsibilities

Technical Leadership

• Lead endtoend 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 performanceoptimized data pipelines.
• Act as the primary technical escalation point for datarelated issues.

ETL & Data Engineering

• Design and implement Matillion/Snowflake ETL pipelines for structured and semistructured data.
• Build reusable, metadatadriven transformation frameworks.
• Optimize data loads, transformations, and Snowflake performance.
• Ensure data quality, consistency, and reconciliation across pipelines.

Automation & DevOps

• Drive automationfirst approach across:
  • ETL deployments
  • Validation and reconciliation
  • Regression and data sanity checks
• Enable CI/CD pipelines for data platforms (Git, automated deployments, environment promotion).
• Collaborate with DevOps teams to enforce coding standards and release controls.
• Reduce manual intervention through robust automation and monitoring.

Data Architecture & Modeling

• Design and maintain:
  • Enterprise data warehouse schemas
  • Fact and dimension models
  • Conformed layer structures
• Partner with Data Architects to align logical and physical models.
• Ensure scalability, extensibility, and performance of data structures.

Agile Delivery & Collaboration

• Lead data engineering workstreams in Agile sprints.
• Support backlog grooming, estimation, and technical story readiness.
• Collaborate with:
  • API teams for data consumption
  • Salesforce/UI teams for downstream enablement
  • QA for test data, automation, and validation strategy
• Actively participate in sprint ceremonies and technical reviews.

Governance & Quality

• Enforce data engineering best practices and standards.
• Ensure adherence to security, compliance, and data governance guidelines.
• Proactively identify risks, dependencies, and technical gaps.
• Contribute to RAID management and mitigation plans.

Required Skills & Experience

Must Have

• 10+ years of experience in Data Engineering / BI / Data Platforms /Snowflake
• Strong handson experience with Matillion/Snowflake
• Strong SQL expertise and database design / data modeling
• Experience with data transformations, largescale ETL pipelines
• Strong automation mindset and implementation experience
• Experience with cloud data platforms (Snowflake preferred)
• Agile delivery experience

Good to Have

• CI/CD for data platforms (ADO, Git, deployment automation)
• API data integration experience
• Data quality frameworks and monitoring
• Experience in healthcare, insurance, or enterprise data domains