Data Engineer Airflow Jobs in Texas (NOW HIRING)

Provides technical and strategic leadership for the County's data engineering function, overseeing the design, development, and delivery of scalable data systems and services. Defines engineering standards, leads complex cross-functional projects, and ensures the reliability, performance, and security of data pipelines. Guides modernization efforts, mentors engineering staff, and serves as a key contributor to the County's enterprise data and analytics strategy.Established in 1846, Dallas County is committed to serving the community through innovation, transparency, and efficiency

As the second largest county in Texas, we provide a wide range of services to support the safety, health, and well-being of our residents. From public safety and justice to health services and infrastructure, our team is dedicated to fostering a thriving, inclusive, and resilient community. With a focus on operational excellence and a commitment to continuous improvement, Dallas County works to deliver the highest quality services that enhance the lives of all who live, work, and visit here.Education, Experience and Training: Education and experience equivalent to a Bachelor's degree from an accredited college or university in Computer Science, Software Engineering, or a related field

Master's degree preferred. Six (6) years of experience in data engineering, cloud platforms, or AI-driven data processing, with two (2) years in a technical leadership role. Certifications (Preferred): Cloud data platforms (e.g., Azure Data Engineer, AWS Big Data, GCP Professional Data Engineer) Airflow, Snowflake, Databricks, or similar platform Special Requirements/Knowledge, Skills & Abilities: 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." Physical/Environmental Requirements: Occasional travel to County sites, vendor meetings, conferences, and industry events.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.