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. #LI-JP1Responsibilities 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 The New York Power Authority is committed to providing fair, competitive, and market-informed compensation. The estimated salary range for this position is: $102,000 – $128,000. The salary offered will be determined based on the successful candidates’ relevant experience, knowledge, skills, and abilities. The New York Power Authority and Canal Corporation believes that diversity, equity, and inclusion drive our success, and we encourage women, people of color, LGBTQIA+ individuals, people with disabilities, members of ethnic minorities, foreign-born residents and veterans to apply. As an equal opportunity employer, NYPA/Canals is committed to building inclusive, innovative work environments with employees who reflect communities across New York and enthusiastically serve them. We proudly celebrate diversity and do not discriminate based on race/color, creed/religion, national origin, citizenship or immigration status, age, disability, military status, gender/sex, sexual orientation, gender identity/expression, pregnancy and related conditions, familial/marital status, domestic violence victim status, predisposing genetic characteristics, arrest/criminal conviction record or any other category protected by law. NYPA/Canals will also provide reasonable accommodations during the hiring process related to candidates’ disabilities, pregnancy-related conditions, religious observances/practices and/or domestic violence concerns. To request an accommodation, please email View email address on click.appcast.io.