Data Architect 100% Remote

Data Architect 100% RemoteRequirementsNYS utility experience is strongly preferred.If candidates do not have New York utility experience, candidates with experience working for other state utilities will also be considered.Data Development Lead Role Overview [10+ Years, Preferably Utilities (NYS) and Data Architect Roles with Azure Databricks and C3.ai including AMI and Customer Data]Responsible for data engineering, analytics enablement, and data governance support across the BEUP 3.0 program. This role reports to the Solution/Technical Architect and works closely with product ownership, application engineering, Enterprise Architecture, Cloud Services, and InfoSec.Minimum Required Qualifications Senior-level experience leading data development efforts in a team lead or lead engineer capacityStrong hands-on expertise in: SQL development, optimization, and troubleshooting Data modeling (conceptual, logical, and physical; dimensional modeling for analytics where applicable) Data integration patterns (ETL/ELT, batch and event-driven ingestion) Data quality profiling, validation rules, reconciliation, and exception handling Experience implementing data solutions in cloud environments, including familiarity with cloud-native data and analytics services (managed databases, object storage, orchestration, streaming and queues, monitoring and logging) Demonstrated ability to operate effectively with legacy data, including inconsistent definitions, incomplete normalization, and data quality gaps Scope Of Responsibilities Leading design and implementation of data ingestion, transformation, and persistence patterns aligned to a defined solution architecture Developing and maintaining robust, testable data pipelines with appropriate observability (logging, monitoring, alerting) Establishing development standards for data code including SQL, transformations, and orchestration, with peer review and performance tuning practices Partnering with application teams to define and implement reliable data interfaces including APIs, extracts, and event or message-based integrations Producing and maintaining data documentation including pipeline specifications, data dictionaries, lineage summaries, and data quality rule documentationAnalytics enablementShaping datasets for reporting and operational analytics consumption Defining and documenting business metrics, calculations, and dataset expectations in collaboration with business stakeholders Ensuring analytic outputs are traceable to source data and aligned to approved definitions Data governance & controlsSupporting data governance objectives including data definitions, business glossary alignment, metadata documentation, and lineage capture Engaging data owners and stewards in operational governance workflows Implementing and validating data access controls consistent with security requirements, including role-based access, least privilege, and auditing Contributing to governance reviews with artifacts such as data flows, controls, data quality rules, and lineage summaries Data quality, risk & issue managementIdentifying data risks early (quality, completeness, timeliness, duplication, referential integrity) and proposing remediation options Creating practical approaches to manage known data imperfections, including tolerant processing, exception queues, and reconciliation reports Communicating constraints and tradeoffs clearly, and recommending alternative approaches when requests are not feasible