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Lead Data Analytics Engineer Jobs in Texas (NOW HIRING)

Tixy Services LLC

Lead Data Engineer

Dallas, TX · On-site

$113K - $136K/yr

Lead the analysis, design, development, and implementation of scalable data solutions within the Enterprise Data Warehouse and modern data platform. * Partner with Product Engineers, Data Engineers ...

Trideum

Data Scientist/Analytics Engineer

Killeen, TX · On-site

Data Scientist/Analytics Engineer Full-time Killeen, TX About Us Trideum Corporation is a 100% employee-owned company, committed to embracing the worlds toughest challenges with a servants heart.

Varidesk LLC

Analytics Engineer

Coppell, TX · On-site

... data can drive better decisions * Lead requirements-gathering conversations with business teams ... analytics engineering, BI, or data analyst role with demonstrable statistical depth * Strong ...

New

Wells Fargo

Lead Data Engineer

Irving, TX

$98K - $129K/yr

Support advanced analytics, AI-enabled services, and enterprise reporting solutions through well-architected data services. * Lead technical design activities, architecture reviews, and engineering ...

New

1 point system

Lead Data Engineer

Dallas, TX · On-site

$101K - $133K/yr

We're looking for a Lead Data Engineer to own the design and evolution of our modern data platform ... Partner with business, product, analytics, and data science teams to translate requirements into ...

Indigo Beam

Analytics Engineer

Houston, TX · On-site

This position combines strong SQL development, data engineering, data warehousing, semantic modeling, and analytics expertise to ensure reliable, scalable, and high-quality data is available to ...

Vistra Corp

Lead Data Analyst

Irving, TX · On-site

Key Accountabilities Developing and implementing data strategy and analytics initiatives that align ... Advanced experience in SQL programming, statistical analysis and data modeling Extensive experience ...

Vistra Energy

Lead Data Analyst

Irving, TX · Hybrid

Key Accountabilities Developing and implementing data strategy and analytics initiatives that align ... Advanced experience in SQL programming, statistical analysis and data modeling Extensive experience ...

TXU Energy

Lead Data Analyst

Irving, TX · Hybrid

Key Accountabilities Developing and implementing data strategy and analytics initiatives that align ... Advanced experience in SQL programming, statistical analysis and data modeling Extensive experience ...

National Trench Safety, LLC

Analytics Engineer

Houston, TX · On-site

$109K - $131K/yr

The Analytics Engineer will own the layer between raw data and finished reporting, combining SQL data modeling with Power BI semantic models and dashboards. This hybrid role partners with the Sr. ...

National Trench Safety, Inc

Analytics Engineer

Houston, TX · On-site

$99K - $118K/yr

J ob Summary The Data & Analytics team builds the reporting and data infrastructure that supports company-wide decision-making. The Analytics Engineer will own the layer between raw data and finished ...

First Citizens Bank

Lead Data Engineer

Austin, TX · Remote

$113K - $136K/yr

We are seeking an experienced Lead Data Engineer to join our Data Platform Engineering Organization ... Partner with business stakeholders, analysts, and technology teams to translate business ...

Vistra Corp.

Lead Data Analyst

Irving, TX · On-site

Key Accountabilities • Developing and implementing data strategy and analytics initiatives that ... programming, statistical analysis and data modeling • Extensive experience in statistical ...

National Trench Safety

Analytics Engineer

Houston, TX · On-site

$109K - $131K/yr

The Analytics Engineer will own the layer between raw data and finished reporting, combining SQL data modeling with Power BI semantic models and dashboards. This hybrid role partners with the Sr. ...

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All JobsLead Data Analytics Engineer JobsLead Data Analytics Engineer Jobs in Texas

Lead Data Analytics Engineer information

What does a Lead Data Analytics Engineer do?

A Lead Data Analytics Engineer oversees the design, development, and maintenance of data analytics systems within an organization. They lead teams to build data pipelines, optimize data workflows, and ensure data quality and accessibility for business insights. Their role often involves collaborating with data scientists, analysts, and stakeholders to translate business requirements into technical solutions. Additionally, they are responsible for setting best practices, mentoring team members, and staying updated with emerging technologies in data engineering.

What are the key skills and qualifications needed to thrive as a Lead Data Analytics Engineer?

To thrive as a Lead Data Analytics Engineer, you need advanced expertise in data modeling, statistical analysis, and programming, typically supported by a degree in computer science, statistics, or a related field. Mastery of tools such as SQL, Python, R, cloud platforms (like AWS or Azure), and data visualization software, along with certifications like AWS Certified Data Analytics or Google Professional Data Engineer, is highly valued. Strong leadership, problem-solving, and communication skills help you guide teams and translate complex data insights to stakeholders. These competencies are essential for delivering impactful analytics solutions and driving data-driven decision-making within organizations.

How does a Lead Data Analytics Engineer typically collaborate with cross-functional teams?

A Lead Data Analytics Engineer frequently partners with data scientists, business analysts, and software engineers to design and implement scalable analytics solutions. They often act as a bridge between technical teams and business stakeholders, translating business requirements into actionable data models and pipelines. Effective communication and project management skills are crucial in ensuring alignment on goals, timelines, and deliverables. Regular meetings and agile workflows are common, fostering a collaborative environment that supports innovation and timely project delivery.

What is the difference between Lead Data Analytics Engineer vs Data Scientist?

AspectLead Data Analytics EngineerData Scientist
CredentialsBachelor's or Master's in Data Science, Computer Science, or related fields; certifications like AWS, Azure, or Google CloudBachelor's or Master's in Data Science, Statistics, or related fields; similar certifications
Work EnvironmentFocus on data infrastructure, pipelines, and analytics tools; often in engineering teamsFocus on statistical modeling, machine learning, and data interpretation; often in research or analytics teams
Employer & Industry UsageUsed in tech, finance, healthcare for building data systems and analytics platformsUsed across industries for predictive modeling, research, and insights generation

The main difference is that Lead Data Analytics Engineers primarily focus on building and maintaining data infrastructure and analytics pipelines, while Data Scientists concentrate on analyzing data, creating models, and deriving insights. Both roles require strong technical skills and often overlap, but their core responsibilities differ in scope and focus.

What cities in Texas are hiring for Lead Data Analytics Engineer jobs?

Cities in Texas with the most Lead Data Analytics Engineer job openings:

Infographic showing various Lead Data Analytics Engineer job openings in Texas as of August 2026, with employment types broken down into 85% Full Time, and 15% Contract. Highlights an 71% In-person, 2% Hybrid, and 27% Remote job distribution.

Lead Data Engineer

Dallas, TX • On-site

Tixy Services LLC
See more jobs at Tixy Services LLCexternal

$113K - $136K/yr

Other

This job post has expired today. Applications are no longer accepted.

Key responsibilities

  • Lead the analysis, design, development, and implementation of scalable data solutions within the Enterprise Data Warehouse and modern data platform.

  • Design, build, optimize, and support ETL/ELT pipelines using Snowflake, Nexla, SQL, Python, and related data integration technologies.

  • Support the implementation of metadata management, data lineage, data observability, and data governance practices required for enterprise AI initiatives.

Job description

Job Description:
The Lead Data Engineer will lead and support the design, development, and delivery of complex data engineering and AI-ready data solutions across the enterprise data ecosystem. This role will work closely with Product Engineers, Data Engineers, business-facing leads, architects, Data Scientists, AI Engineers, and cross-functional stakeholders to translate business needs into scalable data and AI solutions.
 
The successful candidate will bring strong hands-on experience with Snowflake data warehouse, ETL/ELT tools such as Nexla, workflow orchestration platforms such as Apache Airflow, and modern AI-powered development tools including Microsoft Copilot, Claude, and other GenAI platforms. The ideal candidate will understand how to design data foundations that support analytical workloads, machine learning, large language models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks.
 
This role is expected to help manage team priorities within Agile sprints, coordinate effectively across onsite, offsite, offshore, and cross-team members, and drive the adoption of AI-assisted engineering practices that improve productivity, quality, and delivery speed.
 
Position Responsibilities:
  • Lead the analysis, design, development, and implementation of scalable data solutions within the Enterprise Data Warehouse and modern data platform.
  • Partner with Product Engineers, Data Engineers, business-facing leads, architects, Data Scientists, AI Engineers, and stakeholders to understand requirements, clarify priorities, and deliver business-aligned data and AI solutions.
  • Design, build, optimize, and support ETL/ELT pipelines using Snowflake, Nexla, SQL, Python, and related data integration technologies.
  • Develop and manage Apache Airflow jobs, DAGs, and schedules to ensure reliable, observable, and timely data processing across platforms.
  • Design and implement AI-ready data architectures that support analytics, machine learning, generative AI, RAG, vector databases, and Agentic AI solutions.
  • Leverage AI-assisted development tools such as Microsoft Copilot, Claude, Cursor, and similar platforms to accelerate development, improve code quality, automate documentation, and enhance engineering productivity.
  • Collaborate with AI/ML teams to define data ingestion, transformation, governance, and serving patterns required for AI model training and inference workloads.
  • Support the implementation of metadata management, data lineage, data observability, and data governance practices required for enterprise AI initiatives.
  • Evaluate and recommend emerging AI technologies, frameworks, and best practices that improve data engineering capabilities and operational efficiency.
  • Support Agile delivery by helping manage sprint priorities, backlog refinement, story estimation, daily execution, dependency tracking, and delivery commitments.
  • Coordinate work across onsite, offsite, offshore, and cross-team members to align scope, resolve blockers, and maintain delivery momentum.
  • Create and maintain technical design documentation, data flow diagrams, AI solution architecture diagrams, operational runbooks, and implementation plans for assigned solutions.
  • Drive data quality, performance tuning, monitoring, troubleshooting, and production support for critical data pipelines, AI data services, and Snowflake workloads.
  • Lead technical discussions, architecture reviews, code reviews, root-cause analysis, and problem-solving sessions with engineering, AI, and business partners.
  • Mentor team members on modern data engineering practices, AI-assisted development methodologies, and emerging AI technologies.
  • Promote responsible AI practices, including data privacy, security, governance, compliance, and ethical use of AI solutions.
Required Skills, Knowledge and Experience:
  • Bachelor''s degree in Computer Science, Information Technology, Engineering, Data Analytics, Data Science, Artificial Intelligence, or a related technology field, or equivalent job-related experience.
  • Strong hands-on experience with Snowflake data warehouse, including SQL development, performance tuning, data modeling, stored procedures, and scalable data processing patterns.
  • Hands-on experience designing and supporting ETL/ELT pipelines using Nexla and related modern data integration tools.
  • Experience with Apache Airflow or similar job scheduling and workflow orchestration tools, including DAG development, scheduling, monitoring, and troubleshooting.
  • Strong proficiency in SQL and Python for enterprise-scale data engineering solutions.
  • Practical experience using AI-powered development platforms such as Microsoft Copilot, Claude, Cursor, GitHub Copilot, or similar tools to improve engineering productivity and delivery outcomes.
  • Understanding of modern AI and Generative AI concepts, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector embeddings, prompt engineering, and Agentic AI patterns.
  • Experience designing data architectures and pipelines that support AI, machine learning, analytics, and intelligent automation use cases.
  • Knowledge of data governance, security, privacy, lineage, and compliance requirements related to AI and enterprise data platforms.
  • Ability to lead sprint execution, manage competing priorities, clarify scope, identify risks, and coordinate delivery across multiple technical and business stakeholders.
  • Strong collaboration skills with Product Engineering, Data Engineering, AI/ML Engineering, BI/Analytics, QA, Architecture, and business-facing teams.
  • Experience working with onsite, offsite, offshore, and distributed team members in an Agile delivery environment.
  • Strong analytical, problem-solving, communication, and troubleshooting skills.
  • Self-starter with strong ownership, accountability, attention to detail, and ability to operate independently in a fast-paced environment.
  • Demonstrated ability to learn and adopt emerging AI technologies and frameworks in a rapidly evolving technology landscape.
Preferred but Not Required:
  • Experience with Snowflake on Azure and related Azure data services.
  • Experience with Azure OpenAI, Microsoft Fabric, Databricks, Amazon Bedrock, Anthropic Claude, OpenAI, or similar AI platforms.
  • Experience implementing Retrieval-Augmented Generation (RAG), semantic search, vector databases, AI agents, or Agentic AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar technologies.
  • Experience building AI-enabled data products, intelligent document processing solutions, conversational AI, or enterprise knowledge retrieval systems.
  • Experience with additional ETL/ELT tools such as Azure Data Factory, Talend, Python-based frameworks, or similar technologies.
  • Experience with DevOps, CI/CD, Infrastructure-as-Code, and MLOps practices supporting AI and data platform deployments.
  • Experience with Jira, Azure DevOps, GitHub, or similar Agile delivery and project tracking tools.
  • Experience supporting enterprise data platforms, data quality frameworks, data governance, metadata management, or Master Data Management initiatives.
  • Experience in the insurance, healthcare, or financial services industry.
  • Relevant certifications in Snowflake, Azure, Generative AI, Claude, Microsoft Copilot, AI Engineering, or Cloud Data Platforms.
 

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