About the Role:

The Data Engineer designs, develops, and maintains NYSTEC's enterprise data platform and data integration solutions. This role builds scalable, secure, and high-performing data pipelines, data warehouses, lakehouses, and related data solutions that support reporting, analytics, artificial intelligence initiatives, and data-driven decision-making. The position works closely with the Business Intelligence team, internal technology teams, and business stakeholders to integrate data from multiple systems, improve data quality and governance, and support the continued maturity of NYSTEC's enterprise data platform.

Key Responsibilities

Design, develop, and maintain scalable enterprise data pipelines that support the organization's data integration, analytics, and business intelligence initiatives.
• Design, implement, and support enterprise data architecture, including data warehouses, lakehouses, and other analytical data repositories.
• Develop and maintain robust ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes to ingest, transform, validate, and deliver data from multiple internal and external business systems.
• Design and implement logical and physical data models that promote consistency, scalability, and long-term maintainability.
• Develop, test, deploy, and maintain data engineering solutions that leverage SQL, Python, and PySpark to support enterprise data processing and automation.
• Integrate data from enterprise applications, APIs, relational databases, flat files, and third-party systems while ensuring data integrity and reliability.
• Implement and maintain enterprise data governance standards, including data quality, metadata management, lineage, security, and access controls.
• Monitor, troubleshoot, and optimize enterprise data pipelines, databases, and platform performance to ensure reliability, scalability, and operational efficiency.
• Collaborate with business stakeholders, application owners, and technical teams to translate business requirements into scalable data solutions.
• Develop and maintain technical documentation, including solution architecture, operational procedures, and development standards.
• Evaluate emerging technologies and recommend improvements that enhance the organization's enterprise data platform, data engineering practices, and overall data maturity.
• Partner with Business Intelligence team members to ensure enterprise data assets effectively support reporting, advanced analytics, artificial intelligence, and self-service data initiatives.
• Participate in platform planning, architecture reviews, and continuous improvement efforts to ensure the enterprise data platform remains secure, scalable, and aligned with organizational objectives.

About you:

Required Qualifications
• Experience developing enterprise data solutions using Microsoft Fabric. Candidates with
equivalent experience using Microsoft Azure Data Factory, Azure Data Lake Storage, Azure SQL, SQL Server Integration Services (SSIS), SQL Server, or related Microsoft data services in cloud or on-premises environments will also be considered.
• Advanced SQL development skills, including query optimization, database design, and
performance tuning.
• Strong proficiency in Python and/or PySpark for data engineering, automation, and data
transformation.
• Experience designing and developing ETL/ELT solutions and enterprise data integration
processes.
• Experience designing and supporting relational databases, data warehouses, lakehouses, and enterprise analytical data models.
• Experience integrating data from enterprise applications, APIs, relational databases, flat files, and cloud services.
• Strong understanding of enterprise data architecture, data modeling, data governance, metadata management, and security best practices.
• Experience implementing source control, testing, deployment, and operational support practices for enterprise data solutions.
• Excellent analytical, troubleshooting, organizational, and communication skills.

Preferred/Desired Qualifications

• Experience supporting enterprise Business Intelligence, analytics, and AI initiatives through modern data engineering practices.
• Experience implementing data governance, security, and performance optimization within Microsoft enterprise data platforms.
• Microsoft Certified: Fabric Analytics Engineer Associate (DP-600), Azure Data Engineer Associate (DP-203), or similar Microsoft certification preferred.

Education and Experience

• A bachelor's degree in computer science, information systems, data engineering, information technology or a related discipline and five years of related experience designing, developing and supporting enterprise platforms.
• An equivalent combination of advanced education, training, and experience will be considered.

The target base salary for this position is $97,172.00 to $126,323.00 per year. When determining compensation, we analyze and carefully consider several factors, including skill set, experience, location, and job-related qualifications