Data Engineer 3

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.Education, Experience and Training: Education and experience equivalent to a Bachelor's degree from an accredited college or university in Computer Science, Information Systems, Data Analytics, or in a job-related field of study. Five (5) years of job-related experience in data engineering, data analytics, or AI/ML data processing. Certifications (Preferred): • Microsoft Certified: Azure Data Engineer Associate • AWS Certified Data Analytics – Specialty • Snowflake or Databricks certification Special Requirements/Knowledge, Skills & Abilities: • Ability to be analytical and problem-solve • Ability to lead technical design discussions and mentor others • Knowledge of performance, scalability, and data governance best practices • Skill in written and verbal communication across technical and business stakeholders • Skill in SQL and data modeling expertise (dimensional and relational) • Skill in data platforms such as Azure Data Factory, Databricks, Snowflake, or AWS Glue • Skill in Python, Spark, or similar languages for data processing • Knowledge of Agile, DevOps, CI/CD, and version control tools • Skill in SQL, Python, and modern data platforms (e.g., Azure Data Factory, AWS Glue, dbt, Airflow) • Skill in cloud data warehouses (e.g., Snowflake, BigQuery, Synapse) and orchestration tools • Knowledge of ML pipelines, streaming frameworks (e.g., Kafka, Spark Streaming), and data APIs • Knowledge of architecture, performance optimization, and automation • Skill in collaboration and communication with both technical and non-technical stakeholders • Ability to lead delivery of complex solutions while balancing scalability and maintainability • Ability to work in a fast-paced, evolving technology environment.  Must possess a valid Texas Driver’s License and good driving record. Will be required to provide a copy of 10-year driving history. Must maintain a good driving record and remain in compliance with Article II, Subdivision II of Chapter 90 of the Dallas County Code. “Individuals holding or considered for a position which has, or may have, access to criminal justice databases including the FBI Criminal Justice Information Systems, NCIC/TCIC and similar databases, must pass a national fingerprint-based records check prior to placement in such position and may be denied placement in such positions and/or access to such systems. Individuals must also maintain the ability to pass the records check while in the position or until such time that the Commissioners Court and the County Civil Service Commission deem this position no longer has this requirement.” Physical/Environmental Requirements: Occasional travel to County sites and industry conferences. 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-communicated to stakeholders and downstream users. Performs other duties as assigned.

Minimum Salary: 8180.55

Maximum Salary: 10225.71