Senior Data Engineer - GCP, BigQuery, Airflow, Spring Boot

Factspan; Atlanta (GA); On-site; USD 120,000 - 150,000; Full time

Job summary

Factspan in Atlanta, GA is seeking an experienced Data Engineer to join the MarTech Data Engineering POD. You will design and build scalable data pipelines that ingest, transform and load data from BigQuery into MongoDB, using Airflow and Dataflow in GCP.

The role emphasizes reliability, performance, and production readiness. You will collaborate with Lead Data Engineer and SMEs to translate requirements into robust data pipelines, support testing, and participate in agile ceremonies.

Qualifications

• Proficient in Java with Spring Boot applications.
• Strong experience with Google Cloud Platform services: BigQuery, Dataflow, Cloud Composer (Airflow).
• SQL proficiency for profiling, transformation, and performance tuning.
• Python for pipeline automation and orchestration.
• Experience building batch and streaming data pipelines.
• Exposure to marketing/customer engagement platforms is a plus.

Responsibilities

• Design and develop data ingestion, transformation, and orchestration pipelines using GCP and Airflow.
• Implement and maintain data integrations between MongoDB and BigQuery for performance and scalability.
• Build and optimize ETL/ELT workflows for data orchestration and warehousing.
• Implement data quality checks, monitoring, and alerting frameworks.
• Collaborate with Lead DE and SMEs to translate requirements into data pipelines.
• Support performance tuning, data reconciliation, and defect resolution during testing.
• Participate in daily Agile ceremonies, sprint reviews, and deployment planning.

Skills

Java

Spring Boot

Google Cloud Platform

BigQuery

SQL

Python

Airflow

Apache Beam

Education

Bachelor's or Master’s degree in Computer Science, Information Technology, or a related field

Tools

MongoDB

Dataflow

Cloud Composer

GCS

Job description

Factspan in Atlanta, GA is seeking an experienced Data Engineer to join the MarTech Data Engineering POD. You will design and build scalable data pipelines that ingest, transform and load data from BigQuery into MongoDB, using Airflow and Dataflow in GCP.

The role emphasizes reliability, performance, and production readiness. You will collaborate with Lead Data Engineer and SMEs to translate requirements into robust data pipelines, support testing, and participate in agile ceremonies.