Data Engineer

GCS Recruitment; Norristown (GA); On-site; USD 110,000 - 150,000; Full time

Job summary

GCS Recruitment is seeking an experienced Data Engineer to design and optimize scalable data platforms supporting analytics and reporting. This position collaborates with cross-functional teams, develops high-performance data solutions, and drives engineering best practices.

The ideal candidate has 8+ years of experience and a Master's degree in a related field. The role requires advanced knowledge of SQL, Python, and cloud platforms such as AWS. Candidates should also possess strong expertise in Snowflake and modern ELT frameworks.

Qualifications

• 8+ years of experience in Data Engineering or related fields.
• Advanced SQL and Python development experience.
• Strong expertise with Snowflake, dbt, Airflow, and modern ELT frameworks.
• Experience designing dimensional models and enterprise‑scale data warehouses.
• Hands‑on experience with Kafka, Spark/PySpark, and streaming data architectures.
• Strong understanding of cloud platforms, particularly AWS.
• Experience with Terraform, Docker, Kubernetes, and CI/CD pipelines.
• Knowledge of data governance, schema evolution, data quality, and observability practices.

Responsibilities

• Design and maintain scalable ELT/ETL pipelines using SQL, Python, dbt, and cloud‑native technologies.
• Build and optimize data warehouse and lakehouse solutions leveraging Snowflake, Databricks, and AWS services.
• Develop dimensional data models and analytics‑ready datasets to support business intelligence and advanced analytics.
• Implement data quality, monitoring, and observability frameworks to ensure data reliability and trust.
• Build and support batch and near‑real‑time data pipelines using Kafka, Spark, and Airflow.
• Optimize platform performance, scalability, and cost across data infrastructure and workloads.
• Collaborate with cross‑functional stakeholders to translate business requirements into scalable data solutions.
• Drive CI/CD, infrastructure‑as‑code, and engineering best practices across the data platform.
• Mentor junior engineers and contribute to technical leadership, architecture decisions, and code reviews.

Skills

Advanced SQL

Python

Snowflake

dbt

Airflow

Kafka

Spark/PySpark

AWS

Terraform

Docker

Kubernetes

Education

Master's degree in Mathematics, Computer Science, Engineering, or related field

Job description

We are seeking an experienced Data Engineer to design, build, and optimize scalable data platforms that support analytics, reporting, and data‑driven decision‑making across the organization. This role will partner closely with Product, Analytics, Data Science, and Engineering teams to develop reliable, high‑performance data solutions and drive best practices in modern data engineering.

Key Responsibilities

• Design and maintain scalable ELT/ETL pipelines using SQL, Python, dbt, and cloud‑native technologies.
• Build and optimize data warehouse and lakehouse solutions leveraging Snowflake, Databricks, and AWS services.
• Develop dimensional data models and analytics‑ready datasets to support business intelligence and advanced analytics.
• Implement data quality, monitoring, and observability frameworks to ensure data reliability and trust.
• Build and support batch and near‑real‑time data pipelines using Kafka, Spark, and Airflow.
• Optimize platform performance, scalability, and cost across data infrastructure and workloads.
• Collaborate with cross‑functional stakeholders to translate business requirements into scalable data solutions.
• Drive CI/CD, infrastructure‑as‑code, and engineering best practices across the data platform.
• Mentor junior engineers and contribute to technical leadership, architecture decisions, and code reviews.

Required Skills

• 8+ years of experience in Data Engineering or related fields.
• Advanced SQL and Python development experience.
• Strong expertise with Snowflake, dbt, Airflow, and modern ELT frameworks.
• Experience designing dimensional models and enterprise‑scale data warehouses.
• Hands‑on experience with Kafka, Spark/PySpark, and streaming data architectures.
• Strong understanding of cloud platforms, particularly AWS.
• Experience with Terraform, Docker, Kubernetes, and CI/CD pipelines.
• Knowledge of data governance, schema evolution, data quality, and observability practices.

Qualifications

• Experience supporting analytics, product, marketplace, ecommerce, or customer data platforms.
• Exposure to Databricks and multi‑cloud environments.
• Background partnering with Data Science, Product, and Analytics teams.
• Master's degree in Mathematics, Computer Science, Engineering, or a related quantitative field.

GCS is acting as an Employment Business in relation to this vacancy.