Python Engineer

Matlen Silver; Jersey City (NJ); On-site; USD 120,000 - 160,000; Full time

Job summary

Matlen Silver is seeking a Data Engineer to join the Enterprise Finance Technology (ADAPT) team. You will help build and support a modern data platform using Python, Apache Airflow, S3-compatible storage, Apache Iceberg, and Starburst.

You will design, develop, and maintain data ingestion and transformation pipelines, onboard new data sources, establish data connectivity, and create curated datasets for analytics.

Qualifications

• 3–5 years of hands-on Python data engineering experience.
• 2+ years of Airflow DAGs in production.
• Experience designing, developing, and supporting data pipelines and automated workflows.
• Experience with S3-compatible object storage platforms.
• Experience creating, managing, and troubleshooting Apache Iceberg tables.
• Experience integrating data from Oracle, SQL Server, and Hive.
• Proficiency with Linux/Unix and shell scripting.
• Experience with Git and collaborative software development practices.
• Understanding of data lakehouse concepts, SQL, and database design.
• Understanding of Agile software development methodologies.
• Excellent written and verbal communication skills.
• Bachelor's degree in a STEM field.

Responsibilities

• Design, develop, and maintain data ingestion and transformation pipelines.
• Build and maintain Apache Airflow DAGs.
• Onboard new data sources and establish data connectivity.
• Create and manage Apache Iceberg tables and curated datasets.
• Develop automated data workflows to replace manual processes.
• Promote data quality, reliability, and operational efficiency.

Skills

Python development

Airflow

Linux/Unix shell

Git/source control

SQL and DB design

Agile methodologies

Analytical problem-solving

Communication skills

Education

Bachelor's degree in Computer Science, Engineering, Mathematics, Information Systems, or related STEM

Tools

Starburst

Trino

Presto

Jenkins

GitHub Actions

Ansible

Hadoop/HDFS

Job description

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.

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.

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.

Required Qualifications

• 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
• 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
• 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

Query Technologies: SQL, Starburst, Trino, Presto

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

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