Data Engineer

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

Location: Atlanta (Onsite)

Experience: 8-10 years

Employment Type: Full Time

About the Project

This role is part of the MarTech Data Engineering POD supporting a Client Facing Java based Spring Boot application. The initiative aims to build a scalable data warehouse solution which aggregates, transforms and loads sales data into MongoDB from Big Query with the help of Airflow and Dataflow. Finally, publish data with the help of Spring Boot application.

Must have:

Tech: Java, Spring Boot, Google Cloud Platform, Big Query, SQL, Python, Airflow, Apache Beam

Key Responsibilities:

• Design and develop data ingestion, transformation, and orchestration pipelines using Google Cloud Platform (BigQuery, Dataflow, Cloud Composer) and Airflow.
• Implement and maintain data integrations between MongoDB and Big Query, ensuring high performance and scalability.
• Build and optimize ETL/ELT workflows to support data orchestration, transformation and warehousing.
• Implement data quality checks, monitoring, and exception handling frameworks to ensure clean and reliable data.
• Work closely with Lead DE and SME to translate Requirements into data pipelines and orchestration rules.
• Support performance tuning, data reconciliation, and defect resolution during testing and hypercare phases.
• Collaborate with QA team for end-to-end test validation and ensure production readiness.
• Participate in daily Agile ceremonies, sprint reviews, and deployment planning.

Required Technical Skills:

• Must have expertise in Java based Spring Boot Application.
• Strong hands‑on experience in Google Cloud Platform services: BigQuery, Dataflow, GCS, Cloud Composer (Airflow).
• Proficiency in SQL for data profiling, transformation, and performance optimization.
• Proficiency in Python for pipeline automation, scripting, and orchestration.
• Experience building batch and streaming data pipelines.
• Exposure to working with marketing or customer engagement platforms is a plus.
• Understanding data quality, logging, monitoring, and alerting best practices.

Education:

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