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Dallas County · 14 hours ago

1000000567.DATA ENGINEER LEAD.INFO TECH SERVICES

500 Elm St, Dallas, TX, 75202, US

Full-time

Onsite

Senior Level, Lead/Staff

6+ years exp

Dallas County is committed to serving the community through innovation, transparency, and efficiency. They are seeking a Data Engineer Lead to provide technical and strategic leadership for the County’s data engineering function, overseeing the design, development, and delivery of scalable data systems and services.

GovernmentInformation ServicesNon Profit

Responsibilities

Oversees the design and delivery of data pipelines, APIs, and workflows across departments and platforms

Ensures high availability, scalability, and fault tolerance of enterprise data systems

Aligns data services with enterprise SLAs and critical system dependencies

Leads technical implementation of real-time, streaming, and event-based data architectures

Supports data operations through monitoring, logging, and automated incident management

Enforces data governance, access control, and privacy compliance in pipeline delivery

Ensures efficient onboarding of new data sources, systems, and applications

Collaborates with DevOps teams to implement CI/CD and observability pipelines

Maintains operational readiness through automated recovery and version control

Supports data enablement across analytics, dashboards, and AI platforms

Establishes technical standards for data pipeline development, testing, and maintenance

Oversees data workflow orchestration across cloud and on-prem environments

Implements platform observability through metrics, logging, and alerting frameworks

Drives automation of recurring workflows and code deployment processes

Defines strategies for cost management, resource optimization, and scaling of cloud data services

Coordinates with cybersecurity and IT operations on platform compliance and patching

Leads vendor and tool evaluations to improve engineering efficiency and system reliability

Guides containerization, IaC (Infrastructure as Code), and platform provisioning strategies

Manages risks associated with data latency, accuracy, and source system instability

Supports internal audits and compliance assessments related to data workflows

Designs technical architectures for enterprise data pipelines, storage, and integrations

Partners with Data Architects to define shared schemas, domain models, and frameworks

Leads architectural reviews and guide the selection of tools and design patterns

Architect solutions to support distributed, hybrid, and cloud-native data platforms

Evaluates new technologies and approaches for ML Ops, streaming, and open data sharing

Ensures interoperability between data systems, applications, and public-facing services

Drives modularization and reusability of components across departments

Contributes to enterprise blueprints, roadmaps, and modernization initiatives

Aligns data architecture with digital, accessibility, and equity goals

Guides technical solutioning in strategic cross-agency data collaborations

Defines and enforce data quality standards, validation frameworks, and QA practices

Builds automated systems for anomaly detection, metadata validation, and lineage tracking

Guides root cause analysis and long-term resolutions for recurring data issues

Promotes test-driven development, CI/CD, and code review best practices

Drives adoption of monitoring tools to proactively detect and resolve pipeline issues

Ensures all systems meet County standards for privacy, accessibility, and resilience

Leads retrospectives and continuous improvement initiatives across the engineering lifecycle

Optimizes performance of data flows, batch processes, and analytics queries

Reduces manual dependencies through automation and workflow refactoring

Evaluates team tools and recommend improvements to increase velocity and quality

Provides day-to-day technical leadership and mentoring to data engineering staff

Coordinates team assignments, project planning, and workload balancing

Guides onboarding of new team members and support training across tools and platforms

Fosters a team culture centered on innovation, learning, and operational excellence

Promotes diversity and inclusion through equitable leadership and career development

Leads communities of practice focused on data engineering or cloud platforms

Identifies and addresses skill gaps and training opportunities across the team

Partners with management on hiring decisions and organizational planning

Sets and reviews engineering goals, OKRs, and performance metrics

Encourages collaboration across engineering, analytics, and application teams

Acts as the technical point of contact for enterprise data engineering initiatives

Translates stakeholder needs into architecture and delivery roadmaps

Partners with product owners, analysts, and executives to align on data enablement strategy

Coordinates with application teams on integrations, event publishing, and system changes

Supports governance and compliance teams in implementing data controls and lineage

Represents the data team in executive steering committees, RFP development, or vendor assessments

Ensures data delivery timelines, risks, and dependencies are clearly communicated

Participates in public-sector partnerships and cross-agency data collaborations

Supports data literacy efforts by enabling clean, documented datasets for business users

Advocates for the role of data engineering in supporting County priorities and digital equity

Contributes to proposals, RFPs, or funding requests involving enterprise data initiatives

Performs other duties as assigned

Qualification

Data engineeringCloud data platformsData transformationBig data frameworksReal-time data streamingData governanceAIMachine learningCloud-native architectureProblem-solvingCommunicationCollaborationLeadership

Required

Education and experience equivalent to a Bachelor's degree from an accredited college or university in Computer Science, Software Engineering, or a related field

Six (6) years of experience in data engineering, cloud platforms, or AI-driven data processing, with two (2) years in a technical leadership role

Skill in SQL, Python, and/or Scala for data transformation

Skill with big data frameworks (Hadoop, Spark, Databricks, or Flink)

Skill with Azure Data Factory, AWS Glue, or Google Dataflow

Knowledge of real-time data streaming technologies (Kafka, Kinesis, Pub/Sub)

Skill in working with data governance, security, and compliance frameworks

Skill in problem-solving and decision-making

Knowledge of AI, machine learning, and data automation strategies

Ability to design and implement high-performance, scalable data solutions

Skill in leading cross-functional technical teams

Skill in communication and collaboration with executive leadership

Knowledge of cloud-based and hybrid data architectures

Skill in cloud-native data architecture, DevOps, and enterprise analytics enablement

Ability to lead, communicate, and collaborate skills across technical and business teams

Ability to translate strategic goals into scalable engineering delivery

Ability to commit to public-sector innovation, data accessibility, and continuous improvement

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

Preferred

Master's degree preferred

Certifications (Preferred): Cloud data platforms (e.g., Azure Data Engineer, AWS Big Data, GCP Professional Data Engineer), Airflow, Snowflake, Databricks, or similar platform