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Data Leader Jobs in Texas (NOW HIRING)

CG Infinity

Principal Data Engineer

Houston, TX · On-site

We are seeking a Principal Data Engineer to lead the architecture, design, and delivery of modern ... This is a hands-on technical leadership role for someone who can move comfortably between executive ...

CG Infinity

Principal Data Engineer

Dallas, TX · On-site

We are seeking a Principal Data Engineer to lead the architecture, design, and delivery of modern ... This is a hands-on technical leadership role for someone who can move comfortably between executive ...

Openwork

Business Intelligence Manager

The Woodlands, TX · Hybrid

$56 - $58/hr

This role is ideal for a data leader with deep manufacturing expertise who excels at building Tableau dashboards, improving forecasting accuracy, and streamlining commercial systems. Enjoy a ...

Data Analysis Incorporated

Data Architect

Plano, TX · On-site

$61 - $78.50/hr

This role establishes data architecture standards, promotes database design best practices, and provides technical leadership for high-performance relational database environments. The position ...

Amazon

Data Center Cluster Operations Leader

Wink, TX · On-site

Amazon Web Services (AWS) is a fast-paced technology company and a leader in the world of data centers. AWS is growing rapidly, and we are looking for a Senior Manager to join our expanding ...

Amazon

Data Center Cluster Operations Leader

Wink, TX · On-site

Amazon Web Services (AWS) is a fast-paced technology company and a leader in the world of data centers. AWS is growing rapidly, and we are looking for a Senior Manager to join our expanding ...

Amazon

Data Center Cluster Operations Leader

Wink, TX · On-site

Amazon Web Services (AWS) is a fast-paced technology company and a leader in the world of data centers. AWS is growing rapidly, and we are looking for a Senior Manager to join our expanding ...

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All JobsData Leader JobsData Leader Jobs in Texas

Data Leader information

What is a data leader?

A Data Leader is a senior professional responsible for developing and implementing an organization’s data strategy, ensuring that data assets are effectively managed and leveraged to drive business value. They oversee data governance, data quality, analytics initiatives, and often manage teams of data scientists, engineers, and analysts. Data Leaders play a key role in shaping data-driven decision-making, aligning data projects with business objectives, and ensuring compliance with data regulations. Their work helps organizations unlock insights from data, improve operations, and gain a competitive advantage.

What are the key skills and qualifications needed to thrive as a data leader?

To thrive as a Data Leader, you need expertise in data analytics, data management, and strategy, often backed by an advanced degree in a quantitative field and experience in data-centric roles. Familiarity with tools like SQL, Python, data visualization platforms (e.g., Tableau, Power BI), and cloud data systems is typically required. Strong leadership, communication, and stakeholder management skills help drive organizational alignment and data-driven decision-making. These competencies are crucial for shaping effective data strategies, ensuring data quality, and delivering business value through insights.

How do data leaders typically balance strategic oversight with hands-on involvement in data projects?

Data Leaders often face the challenge of balancing high-level strategy with direct involvement in data initiatives. While their primary responsibility is to set the vision for data governance, analytics, and architecture, they also need to stay engaged with teams to ensure alignment and remove obstacles. This often means participating in key project meetings, reviewing major deliverables, and facilitating communication between technical and business stakeholders. Effective Data Leaders delegate operational tasks but remain accessible for critical decision-making and mentorship, fostering both team autonomy and strategic coherence.

What is the difference between Data Leader vs Data Analyst?

AspectData Leader
ResponsibilitiesStrategic data management, setting data vision, leading data teams
Skills & CertificationsData strategy, leadership, advanced analytics, often with certifications like CDMP or DAMA
Work EnvironmentExecutive-level, cross-departmental collaboration, senior management
FocusHigh-level data governance, business impact, long-term data strategy

While a Data Leader focuses on strategic oversight, governance, and leading data initiatives at an organizational level, a Data Analyst primarily handles data analysis, reporting, and supporting decision-making through data insights. Both roles require strong analytical skills, but the Data Leader emphasizes leadership and strategy, whereas the Data Analyst concentrates on technical analysis and data interpretation.

What are popular job titles related to Data Leader jobs in Texas?

For Data Leader jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Data Leader jobs in Texas look for?

The top searched job categories for Data Leader jobs in Texas are:

What cities in Texas are hiring for Data Leader jobs?

Cities in Texas with the most Data Leader job openings:

Data Leader jobs near you
Infographic showing various Data Leader job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 11% Part Time, 4% Contract, and 1% Nights. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Principal Data Engineer

CG Infinity

Houston, TX • On-site

Full-time

Posted 6 days ago

Job description

We are seeking a Principal Data Engineer to lead the architecture, design, and delivery of modern data platforms and analytics solutions for clients. This is a hands-on technical leadership role for someone who can move comfortably between executive-level client conversations, solution architecture, engineering delivery, and mentoring high-performing data teams.
The ideal candidate combines deep data-engineering expertise with strong consulting instincts: they can translate business objectives into scalable technical solutions, communicate complex concepts through clear presentations, and guide teams from discovery through implementation and operationalization.
Key Responsibilities
  • Lead the end-to-end architecture, design, and delivery of enterprise data engineering, data platform, and analytics solutions for client engagements.
  • Serve as a trusted technical advisor to client stakeholders, including technology leaders, data leaders, architects, and business partners.
  • Facilitate discovery sessions, requirements workshops, technical assessments, architecture reviews, and solution-design discussions.
  • Translate business goals, data challenges, and operating-model requirements into practical data strategies, roadmaps, reference architectures, and implementation plans.
  • Define scalable, secure, reliable, and cost-effective architectures for data ingestion, transformation, storage, governance, orchestration, analytics, and data consumption.
  • Remain hands-on in engineering work, including designing data pipelines, reviewing code, building proof of concepts, resolving complex technical issues, and establishing engineering patterns.
  • Architect and implement batch, real-time, streaming, and event-driven data solutions as appropriate for client needs.
  • Design modern cloud data platforms using technologies such as Snowflake, Databricks, Microsoft Fabric, Azure Data Factory, AWS Glue, Amazon Redshift, BigQuery, or equivalent platforms.
  • Lead the development of robust ETL/ELT pipelines, data models, data APIs, semantic layers, and data products.
  • Establish data engineering standards for code quality, testing, CI/CD, observability, metadata management, data lineage, documentation, security, and production support.
  • Drive adoption of DataOps practices, infrastructure as code, automated testing, deployment pipelines, monitoring, and incident-management processes.
  • Partner with data architects, data scientists, analysts, application architects, security teams, and business stakeholders to ensure solutions are aligned to enterprise architecture and business outcomes.
  • Present technical recommendations, architecture options, delivery status, risks, and strategic roadmaps to both technical and executive audiences.
  • Lead client-facing demonstrations, workshops, steering-committee updates, and technical presentations.
  • Mentor senior, mid-level, and junior data engineers; provide technical coaching, career guidance, design feedback, and hands-on support.
  • Lead and influence cross-functional delivery teams, including onshore/offshore engineers, architects, analysts, and client technical resources.
  • Participate in project estimation, staffing, delivery planning, risk management, solution scoping, and proposal development.
  • Support pre-sales and business-development activities, including solutioning, client presentations, technical discovery, RFP responses, estimates, and statement-of-work development.
  • Stay current on emerging data, cloud, AI, governance, and analytics technologies; evaluate where they provide meaningful business value for clients.
Required Qualifications
  • Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field; equivalent professional experience may be considered.
  • 10+ years of progressive experience in data engineering, data warehousing, data integration, data architecture, or related technical disciplines.
  • 3+ years of experience in a technical leadership, lead engineer, solution architect, staff engineer, principal engineer, or consulting leadership capacity.
  • Demonstrated experience architecting and delivering enterprise-scale data platforms and data integration solutions.
  • Strong hands-on expertise in SQL and at least one modern programming language, preferably Python, Scala, Java, or C#.
  • Strong experience with ETL/ELT design, data pipeline development, data transformation frameworks, orchestration, and workflow automation.
  • Experience with one or more cloud providers: Microsoft Azure, AWS, or Google Cloud Platform.
  • Experience with modern cloud data and analytics platforms such as Databricks, Snowflake, Microsoft Fabric, Synapse Analytics, BigQuery, Redshift, or similar technologies.
  • Experience with orchestration and pipeline technologies such as Apache Airflow, Azure Data Factory, AWS Step Functions, dbt, Dagster, Prefect, or equivalent tools.
  • Knowledge of distributed data-processing technologies such as Apache Spark, Kafka, Flink, Hadoop ecosystems, or comparable platforms.
  • Experience designing both batch and near-real-time or streaming data solutions.
  • Strong understanding of dimensional modeling, data vault, normalized data models, lakehouse architectures, data lake architectures, and data warehouse design principles.
  • Experience implementing data quality, data validation, monitoring, lineage, metadata, governance, and security controls.
  • Working knowledge of DevOps and DataOps practices, including Git-based source control, CI/CD, automated testing, deployment automation, and infrastructure as code.
  • Strong understanding of cloud security principles, identity and access management, encryption, secrets management, and role-based access controls.
  • Proven ability to lead architecture discussions and make well-reasoned technical tradeoffs involving performance, scalability, reliability, maintainability, security, and cost.
  • Excellent verbal, written, and presentation skills, with the ability to explain technical concepts clearly to business stakeholders and executive audiences.
  • Experience in a consulting, professional services, systems integrator, or client-facing delivery environment.
Preferred Qualifications
  • Experience designing data platforms that support AI, machine learning, generative AI, retrieval-augmented generation, feature stores, vector databases, or advanced analytics workloads.
  • Certifications in AWS, Azure, Google Cloud, Databricks, Snowflake, Microsoft Fabric, or other relevant data technologies.
  • Experience with master data management, data cataloging, data governance, privacy, regulatory compliance, or data stewardship programs.
  • Experience with tools such as Collibra, Alation, Microsoft Purview, Unity Catalog, Informatica, Monte Carlo, Great Expectations, or similar governance and observability platforms.
  • Experience with Salesforce, SAP, ERP, CRM, finance, supply-chain, healthcare, retail, manufacturing, or other enterprise operational data domains.
  • Familiarity with BI and semantic-layer technologies such as Power BI, Tableau, Looker, ThoughtSpot, or similar platforms.
  • Experience with containerization and cloud-native technologies such as Docker, Kubernetes, Terraform, CloudFormation, Bicep, or Pulumi.
  • Prior experience contributing to proposals, estimates, statements of work, or technical sales pursuits.
  • Experience managing or leading distributed onshore/offshore delivery teams.

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