0000001423.DATA ENGINEER III.7070900.INFO TECH SERVICES

Leads the design and implementation of scalable data pipelines, manages cross-platform data integration, and supports enterprise-wide analytics, reporting, and AI initiatives. Serves as a subject matter expert in modern data engineering tools and cloud services, driving automation, performance optimization, and best practices. Collaborates with analysts, data scientists, application teams, and vendors to deliver high-quality, accessible, and secure data systems that power decision-making and innovation across the County.
Builds and maintains advanced, automated, and scalable data pipelines using cloud-native and on-prem tools. Designs and implements complex ETL/ELT workflows supporting structured, semi-structured, and unstructured data. Optimizes data workflows for performance, reliability, and fault tolerance. Develops and manages reusable data components and infrastructure-as-code assets. Leads testing, deployment, and monitoring of data jobs and platforms. Maintains clear and comprehensive documentation for all data processes and transformations. Ensures secure handling and processing of sensitive or confidential data in compliance with County policies. Troubleshoots and resolve issues related to data integrity, delivery delays, and source changes. Translates enterprise data and analytics requirements into scalable technical designs. Designs and implements data models, APIs, views, and semantic layers for analytics enablement. Contributes to platform modernization efforts (e.g., cloud migration, streaming pipelines, AI integration). Supports solution architecture and technical design of new systems involving data ingestion and storage. Collaborates with data architects and senior leadership on data platform standards and strategy. Guides the selection and implementation of tools for ingestion, orchestration, or transformation. Participates in vendor evaluations, POCs, and technical feasibility assessments. Anticipates system interdependencies and plan for versioning, compatibility, and reuse. Leads implementation of automated data quality checks and validation frameworks. Conducts root cause analysis and remediation for recurring or complex data issues. Monitors data quality metrics and pipeline performance KPIs to drive improvements. Advocates for continuous integration/continuous deployment (CI/CD) and observability in data delivery. Promotes code reuse, modularity, and consistent documentation across the team. Identifies opportunities to reduce technical debt and improve maintainability of legacy workflows. Enforces standards for data encryption, access, classification, and retention. Participates in peer reviews and retrospectives to promote knowledge sharing and improvement. Partners with data scientists, BI developers, analysts, and application teams to deliver integrated data products. Coordinates with DevOps, infrastructure, and security teams to align system and data operations. Serves as a liaison with source system owners to manage schema changes, business rules, and refresh schedules. Works with vendors and consultants on cloud platform architecture and integration patterns. Represents the data engineering team in technical planning, demos, and stakeholder reviews. Collaborates with compliance, audit, or legal teams on data governance and policy enforcement. Participates in enterprise working groups or communities of practice focused on data and analytics. Ensures alignment of data efforts with enterprise architecture and digital transformation goals. Mentors junior engineers and contributes to building internal capabilities and standards. Contributes to technical training materials, team onboarding resources, and knowledge bases. Stays current on trends in streaming data, AI/ML Ops, data lakehouse architectures, and serverless computing. Participates in technology evaluations, conferences, and industry learning opportunities. Leads knowledge-sharing sessions or brown-bag demos within the data community. Pursues advanced certifications (e.g., Databricks, Snowflake, Azure/AWS Data Engineer, dbt). Collaborates on internal tool development and process automation initiatives. Champions diversity, inclusion, and accessibility in data engineering solutions. Translates technical data requirements into actionable plans for delivery and stakeholder use. Supports cross-functional projects by providing impact assessments, design documentation, and data availability estimates. Provides detailed documentation for data dictionaries, transformation logic, and metadata standards. Works with end-users to validate new datasets, pipelines, or visualizations. Presents technical solutions and improvements in a way that aligns with operational goals and metrics. Respond to data requests and serves as a trusted advisor for complex reporting needs. Collaborates with governance teams to ensure traceability, access control, and data classification compliance. Ensures key decisions, risks, and changes are well-communic