Python Engineer

The Data Engineer will design, develop, and maintain data ingestion and transformation pipelines that create governed, scalable, and reusable data products. The engineer will:

• Build and maintain Apache Airflow DAGs
• Onboard new data sources
• Establish and maintain data connectivity
• Create and manage Apache Iceberg tables
• Make curated datasets available for enterprise analytics and reporting
• Develop automated data workflows to replace manual processes
• Promote data quality, reliability, and operational efficiency

The successful candidate will contribute to strategic modernization initiatives and work closely 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.

Candidate should understand how to leverage AI to improve efficiency, AI should not be required for candidates to demonstrate their technical knowledge and skills during the interview process. Please screen candidates accordingly prior to submission., 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., * 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 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 enterprise platforms such as:
• Oracle
• SQL Server
• Hive
• Teradata
• PostgreSQL
• Similar enterprise database platforms
• Proficiency working in Linux/Unix environments, including shell scripting
• Experience with Git/source control 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 methodologies
• Strong analytical, troubleshooting, and problem-solving skills
• Excellent written and verbal communication skills
• Bachelor’s degree in Computer Science, Engineering, Mathematics, Information Systems, or a related STEM discipline

Preferred Skills & 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
• Ansible
• Experience implementing data quality, monitoring, and observability solutions
• Knowledge of data governance, metadata management, and data lineage
• 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
• Exposure to reporting, analytics, AI, or machine learning data platforms

Core Technology Stack

Primary: Python, Apache Airflow, Apache Iceberg, S3/Object Storage, Starburst

Databases & Data Platforms: Oracle, SQL Server, PostgreSQL, Teradata, Hive, HDFS

Query Technologies: SQL, Starburst, Trino, Presto

Development & DevOps: Git, Jenkins, GitHub Actions, Bitbucket Pipelines, Ansible

Infrastructure: Linux/Unix, Kubernetes, OpenShift

Data Engineering: Data Pipelines, Data Lakehouse, Data Quality, Data Governance, Metadata, Data Lineage, Monitoring & Observability