Manager, Data Engineering

BLDG SVC 32 B-J•New York, NY

18h•$140,000 - $150,000

About The Position

Under the direction of the Assistant Director, Health Analytics & Engineering, the Manager, Data Engineering provides technical leadership and oversight for the Health Fund's Data Engineering Team, including the enterprise data warehouse, system integrations, data pipelines, and data governance frameworks. The role leads a team of data engineering professionals responsible for delivering scalable, secure, and high-quality data solutions that support reporting, analytics, operational processes, and strategic initiatives. The Manager, Data Engineering oversees numerous projects and initiatives across the full data lifecycle, including data governance, ETL processes, data validation, standardization and normalization, data integrity and quality assurance/control (QA/QC), data integration, and reporting and dashboard solutions. This position operates at both a technical and business level, helping to delineate roles and responsibilities across the Data Engineering Team while minimizing operational friction and delivering high-quality, reliable technical products in line with business needs and expectations. Working closely with internal teams, including Data Engineering, Analytics, IT, and other stakeholders, as well as external data vendors and content providers, this position drives the delivery of high-quality data products, establishes best practices for data management and governance, and ensures data platforms meet evolving business, regulatory, privacy, and security requirements.

Requirements

Minimum 8 years of experience in data engineering, data warehousing, ETL/ELT development, data integration, or related technical disciplines.
Minimum 3 years of management or supervisory experience leading technical teams and complex data initiatives.
Experience managing projects across the full data lifecycle, including data governance, data quality, integration, testing, documentation, and production support.
Proficiency in SQL and Python, with hands-on industry experience is a must.
Knowledge of API integrations, JSON, XML, SFTP, and file-based data exchanges.
Experience in conducting code review a must; familiarity with unit, integration, and functional testing best practices and procedures preferred.
Strong project management skills a must; familiarity with Agile methodology preferred.
Experience with GitHub is a must; experience with Azure DevOps preferred.
Experience building, maintaining enterprise data pipelines and data stores.
Strong communication and client-facing skills with the ability to work in a centralized technology environment.
Proven ability to lead, coach, mentor, and develop technical staff in a collaborative environment.
Ability to build collaborative relationships across business and technology teams.
Ability to lead organizational change and drive continuous process improvement initiatives.
Strong analytical, problem-solving, and critical-thinking skills.
Strong organizational skills with exceptional attention to detail and follow-through.
Ability to communicate technical concepts to non-technical audiences.

Nice To Haves

Knowledge of healthcare regulatory requirements and data governance standards affecting health benefits organizations preferred.
Familiarity of HIPAA privacy and security requirements and their application to healthcare data environments preferred.
Advanced knowledge of data warehouse design, data modeling, and ETL/ELT methodologies preferred.
Experience with GitHub is a must; experience with Azure DevOps preferred.
Experience in extracting maximum value from low quality and/or error ridden input data preferred.

Responsibilities

Oversee the Data Engineering Team through leadership and supervision. Staff may include Data Engineers, ETL Specialists, and other relevant technical staff.
Provide leadership, coaching, performance management, and professional development to Data Engineering staff, fostering a collaborative, accountable, and high-performing team environment.
Technical ownership of the data warehouse, including system architecture, data architecture, data engineering, and data pipelines
Lead collaboration for the deployment and implementation of tools necessary to integrate data within and across information systems and support data-driven decision making.
Understand business requirements and translate them into technical solutions and application features.
Develop and implement methods to improve data reliability, quality, and accessibility.
Maintain data governance and documentation practices for a variety of data inputs from multiple sources, including flat files and spreadsheet-based files transmitted through SFTP, as well as JSON/XML style objects from API interfaces and other data exchange mechanisms.
Participate in the evaluation and pilot of new technologies and provide recommendations regarding their alignment with business needs and strategic objectives.
Manage communication and relationships with data platform stakeholders, balancing business requirements with technology capabilities.
Partner with business and technology leadership to develop and execute the Health Fund's data strategy, roadmap, and priorities, ensuring alignment with organizational goals and business objectives.
Develop testing protocols to ensure processes are robust and bugs are identified, documented, and resolved.
Conduct functional and non-functional testing.
Evaluate existing data models, architectures, and pipelines.
Develop and maintain technical documentation to accurately represent data models, architectures, integrations, and workflows.
Ensure that integration processes are fully tested and any issues, limitations, integrations, or dependencies are well defined and documented.
Work with cross-functional technology and business partners to lead the technical delivery of integration solutions approved within the portfolio and contribute to the ongoing development of the Funds' data strategy
Collaborate with business partners and internal teams to understand, document, prioritize and implement new datasets, integrations, and features within the data warehouse environment.
Align closely with agency IT teams to support the deployment of integration systems.
Partner with the QA and Infrastructure teams to ensure compliance with regulatory and security requirements.
Establish, maintain, and enforce data engineering standards, policies, procedures, and best practices to ensure data quality, scalability, security, reliability, and operational efficiency.
Monitor and optimize the performance, availability, and reliability of data platforms, data pipelines, data warehouse environments, and integration processes to support business continuity and operational effectiveness.
Collaborate with Data Warehouse Architect in the design for the overall architecture of the data platforms and provide guidance and oversight.
Ensure that guiding principles, technology standards, data governance requirements, and privacy policies are consistently followed.