Associate Data Engineer

Power the Future of New York

At the New York Power Authority, we’re not just part of the energy landscape—we’re leading the charge toward a carbon‑free, resilient, and economically vibrant New York. Our work keeps the state moving, innovating, and thriving.

Summary

We are seeking an Associate Data Engineer to join our growing Data Engineering organization. As NYPA continues to accelerate its data modernization, AI adoption, and cloud‑based product development, this role will play a key part in building scalable data pipelines and supporting enterprise analytics and AI initiatives.

In this hands‑on engineering position, you will design, develop, and maintain data pipelines that power NYPA’s data products, AI platforms, and analytics use cases. You will collaborate closely with senior and lead data engineers, governance teams, and business stakeholders to translate requirements into high‑quality, production‑ready data solutions.

What You’ll Do

• Build, enhance, and debug scalable data pipelines and integrations


• Translate business and technical requirements into data engineering solutions


• Collaborate with lead data engineers and cross functional partners, including AI Fusion teams


• Support development of data products aligned with NYPA’s analytics and AI strategies


• Work with cloud and distributed data processing tools to deliver reliable, high quality data

The successful candidate will demonstrate hands on experience with data pipelines, using tools like Python, PySpark, Azure Data Factory, and Databricks. They will demonstrate strong communication and collaboration skills, and a curiosity for new technology developments.

This is an excellent opportunity for an early career data engineer seeking growth, exposure to modern cloud data technologies, and the chance to contribute directly to NYPA’s digital transformation.

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Responsibilities

• Develop data solutions that are flexible, extensible, elastic, secure and reliable at large scale.


• Work with Lead Data Engineer to provide guidance and direction to project teams ensuring compliance with coding standards and best practices.


• Collaborate with Data Governance team to capture and manage meta data, and implement data quality rules.


• Building and managing data pipelines, data products, integrations and promoting production.


• Develop Application Integrations, APIs and Microservices using hybrid cloud architecture.


• Continuously learn and be at the leading edge of Data/Application Integration, Cloud, Containerization, and other industry trends.


• Work with stakeholders including product, data and business teams to assist with data-related technical issues and support their data infrastructure needs.


• Follow Cyber security guidelines and polices to monitor the company's data security and privacy.


• Build and maintain batch data pipelines for structured and semi-structured data · Support ingestion and preprocessing of unstructured data.


•  Implement basic data quality validations (schema checks, null checks).


• Assist in preparing AI-ready datasets for analytics, AI/ML and GenAI use-cases.


• Support implementation of data contracts through schema validation and data checks.

Knowledge, Skills and Abilities

• Practical experience in traditional and cloud data management components (MS SQL, RDS, Athena, or similar).


• Practical experience in metadata driven ingestion framework, building data pipelines and data sets.


• Working-level familiarity with DevOps and Agile methodologies.


• Strong analytical skills.


• Practical understanding of cloud security policies and concepts. · Exposure to data governance and quality tools.


• Experience with data integration, ETL/ELT orchestration, and application integration using APIs, messaging, or service-based architectures.


• Basic understanding of AI/ML data requirements (training vs inference datasets), structured, semi-structured and unstructured data processing.


• Exposure to streaming concepts, data parsing, text processing.


• Familiarity with data quality and observability concepts.

Education, Experience and Certifications

• Bachelor of Science Degree in MIS or Computer Science/Engineering (or similar) is required.


• Minimum of 2 years of Data Engineering experience.


• Experience developing microservices, serverless components, or distributed data processing solutions.


• Hands-on experience with at least one data integration, data pipelines or application integration platform.


• Practical scripting or programming experience across languages applicable to data engineering workloads.


• Cloud platform certification is preferred.

Physical Requirements

Willingness to travel if necessary