Data Engineer

Pontoonglobal; United States; Remote; USD 120,000 - 150,000; Full time

Job summary

Pontoonglobal is seeking a Data Engineer to build and optimize large-scale data pipelines using PySpark, Scala and Python. The role emphasizes Spark expertise and hands-on data engineering across cloud environments.

You will work remotely from the United States, collaborate with cross-functional teams, implement ETL workflows, and contribute to data quality and performance improvements. Candidates should be comfortable with version control and cloud platforms, and translate business needs into

Qualifications

• Strong hands-on experience with Apache Spark.
• Proficient in PySpark.
• Experience in Scala and Python.
• Knowledge of ETL processes and data pipeline design.
• Understanding of distributed data processing.
• Familiarity with version control tools like Git.
• Basic knowledge of cloud platforms (GCP, AWS, or Azure).

Skills

ETL design

Distributed data processing

Git familiarity

Cloud concepts

Tools

Apache Spark

PySpark

Scala

Python

Git

Cloud platforms basics

Job description

Job Title: Data Engineer (PySpark / Scala / Python)

Location: Remote

Job Description

We are hiring a Data Engineer with strong hands-on experience in PySpark , Scala , and Python . You must have solid expertise in Apache Spark , as it will be the core technology used for building and managing large-scale data processing pipelines. Experience with cloud platforms like Google Cloud Platform (GCP) , Microsoft Azure , or AWS is a plus.

Required Skills:

• Strong hands-on experience with Apache Spark
• Proficient in PySpark
• Experience in Scala and Python
• Knowledge of ETL processes and data pipeline design
• Understanding of distributed data processing
• Familiarity with version control tools like Git
• Basic knowledge of cloud platforms (GCP, AWS, or Azure)

Nice to Have:

• Experience with cloud-native data tools (e.g., Dataproc, Glue, EMR, BigQuery)
• Familiarity with workflow/orchestration tools like Airflow or Cloud Composer
• Experience with CI/CD for data engineering
• Exposure to both structured and unstructured data