Python/S3 Storage Developer (Plano, JC, CLT)

Description

While resources should know how to leverage AI for efficiency, they should not need AI to demonstrate technical knowledge and skills during interview. Please screen accordingly prior to submission.

Role Overview

Enterprise Finance Technology's AI, Data & Platform Services Technology (ADAPT) Team is seeking a motivated Data Engineer to help develop and support a modern enterprise data platform built on Python, Apache Airflow, S3-compatible object storage, Apache Iceberg, and Starburst.

In this role, the candidate will design, develop, and maintain data ingestion and transformation pipelines that create governed, scalable, and reusable data products. The engineer will build Airflow DAGs, onboard new data sources, establish and maintain data connectivity, and create and manage Iceberg tables that make curated datasets available for enterprise analytics and reporting.

The successful candidate will contribute to strategic modernization initiatives by replacing manual processes with automated data workflows while promoting data quality, reliability, and operational efficiency. The role requires close collaboration with platform engineering teams, application owners, and business stakeholders in an Agile environment.

The candidate will function as both an individual contributor and an active member of a globally distributed team.

Requirements

• 3-5 years of hands-on experience developing data engineering solutions using Python.
• 2+ years of experience developing and supporting Apache Airflow DAGs in production environments.
• Experience designing, developing, and supporting data pipelines and automated workflow solutions.
• Experience working with S3-compatible object storage platforms or cloud object storage technologies.
• Experience creating, managing, and troubleshooting Apache Iceberg tables or similar modern table formats.
• Experience connecting to and integrating data from Oracle, SQL Server, Hive, Teradata, PostgreSQL, or similar enterprise platforms.
• Proficiency working in Linux/Unix environments, including shell scripting.
• Experience with source control systems such as Git and collaborative software development practices.
• Understanding of data lakehouse and modern data platform concepts.
• Working knowledge of SQL and database design concepts.
• Understanding of Agile software development methodology.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent written and verbal communication skills.
• Bachelor's degree in Computer Science, Engineering, Mathematics, Information Systems, or related STEM discipline.

Preferred Skills and Experience

• Experience with Starburst, Trino, or Presto.
• Familiarity with Hadoop ecosystem technologies including Hive and HDFS.
• Experience with CI/CD pipelines and automation tools such as Jenkins, GitHub Actions, Bitbucket Pipelines, or Ansible.
• Experience implementing data quality, monitoring, and observability solutions.
• Knowledge of data governance, metadata management, and data lineage concepts.
• Experience supporting large-scale analytical data platforms.
• Exposure to container-based platforms such as Kubernetes or OpenShift.
• Understanding of enterprise security controls, authentication mechanisms, encryption standards, and access management practices.
• Exposure to reporting, analytics, AI, or machine learning data platforms.