Data Engineer

GCS Recruitment

Mount Laurel Township (NJ)

On-site

USD 110,000 - 160,000

Full time

14 days+

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Job summary

GCS Recruitment is seeking an experienced Data Engineer to join the Supply/Yield Data Engineering team to drive data modernization and analytics transformation through 2026. You will design, develop, and maintain data pipelines into Databricks, enable inventory/yield analytics, and support reporting in Tableau Cloud.

We welcome candidates who will migrate Looker assets to Tableau and modernize legacy data solutions, collaborating with engineers to deliver scalable data platforms and robust

Qualifications

  • Strong experience in Data Engineering and ETL/ELT development.
  • Hands-on experience with Databricks.
  • Strong SQL skills with experience working on large datasets.
  • Experience building data pipelines within AWS environments.
  • Experience with Snowflake data warehousing.
  • Experience with Spark/PySpark.
  • Hands-on experience with Terraform and Infrastructure as Code (IaC).
  • Knowledge of CI/CD practices and tools such as GitHub Actions, Concourse, Jenkins, or similar.
  • Experience supporting and troubleshooting production data pipelines.
  • Strong understanding of testing, data quality, and operational support processes.
  • Excellent problem-solving and collaboration skills.

Responsibilities

  • Design, develop, and maintain ETL/ELT pipelines to ingest and transform data into Databricks.
  • Build and support scalable data pipelines using AWS, Databricks, and Snowflake.
  • Work closely with business and technical stakeholders to understand requirements and translate them into robust data solutions.
  • Develop core data assets and datasets that support analytics and reporting consumed through Tableau Cloud.
  • Support the Inventory ART programme by delivering Data Engineering solutions and increasing team capacity during migration activities.
  • Enhance and optimize existing legacy data engineering jobs and processes.
  • Contribute to the migration of reporting solutions from Looker to Tableau.
  • Create and maintain technical documentation, specifications, and implementation guides.
  • Perform testing, validation, and quality assurance activities to ensure data accuracy and reliability.
  • Provide post-delivery support, incident resolution, and troubleshooting for production workloads.
  • Implement Infrastructure as Code (IaC) solutions using Terraform.
  • Build and manage CI/CD pipelines using Concourse or GitHub Actions to enable reliable and automated deployments.
  • Help identify and mitigate risks, including reducing Single Points of Failure (SPOF) through documentation, automation, and knowledge sharing.
  • Collaborate with fellow engineers to establish and promote engineering best practices.

Skills

Data Engineering
ETL/ELT
SQL
Databricks
AWS
Snowflake
Spark/PySpark
Terraform
CI/CD
GitHub Actions
Concourse
Jenkins

Tools

Databricks
GitHub Actions
Concourse
Jenkins
Terraform
AWS
Snowflake
Spark/PySpark

Job description

Job Description

We are looking for an experienced Data Engineer to join the Supply/Yield Data Engineering team and support a large-scale data modernization and analytics transformation programme through 2026.

This role will focus on designing, developing, and maintaining data pipelines that bring data into Databricks, support Inventory and Yield analytics initiatives, and enable business-critical reporting within Tableau Cloud. The successful candidate will also contribute to the migration of reporting assets from Looker to Tableau while helping modernize existing legacy data engineering solutions.

Key Responsibilities
  • Design, develop, and maintain ETL/ELT pipelines to ingest and transform data into Databricks.
  • Build and support scalable data pipelines using AWS, Databricks, and Snowflake.
  • Work closely with business and technical stakeholders to understand requirements and translate them into robust data solutions.
  • Develop core data assets and datasets that support analytics and reporting consumed through Tableau Cloud.
  • Support the Inventory ART programme by delivering Data Engineering solutions and increasing team capacity during migration activities.
  • Enhance and optimize existing legacy data engineering jobs and processes.
  • Contribute to the migration of reporting solutions from Looker to Tableau.
  • Create and maintain technical documentation, specifications, and implementation guides.
  • Perform testing, validation, and quality assurance activities to ensure data accuracy and reliability.
  • Provide post-delivery support, incident resolution, and troubleshooting for production workloads.
  • Implement Infrastructure as Code (IaC) solutions using Terraform.
  • Build and manage CI/CD pipelines using Concourse or GitHub Actions to enable reliable and automated deployments.
  • Help identify and mitigate risks, including reducing Single Points of Failure (SPOF) through documentation, automation, and knowledge sharing.
  • Collaborate with fellow engineers to establish and promote engineering best practices.
Required Skills & Experience
  • Strong experience in Data Engineering and ETL/ELT development.
  • Hands-on experience with Databricks.
  • Strong SQL skills with experience working on large datasets.
  • Experience building data pipelines within AWS environments.
  • Experience with Snowflake data warehousing.
  • Experience with Spark/PySpark.
  • Hands-on experience with Terraform and Infrastructure as Code (IaC).
  • Knowledge of CI/CD practices and tools such as GitHub Actions, Concourse, Jenkins, or similar.
  • Experience supporting and troubleshooting production data pipelines.
  • Strong understanding of testing, data quality, and operational support processes.
  • Excellent problem-solving and collaboration skills.
Nice to Have
  • Experience with Tableau or Tableau Cloud.
  • Experience supporting Looker to Tableau migrations.
  • Experience working within Supply Chain, Inventory, Yield, or Manufacturing domains.
  • Data modelling and analytics engineering experience.
  • Experience modernizing legacy data platforms and applications.
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