Data Architect 100% Remote

Data Architect 100% Remote 

Requirements:

• NYS 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 capacity
  • Strong 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 documentation
• Analytics enablement
  • Shaping 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 & controls
  • Supporting 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 management
  • Identifying 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