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Senior Data Platform Engineer Jobs in Texas (NOW HIRING)

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Lead Data Platform Engineer

Plano, TX · On-site

$95K - $126K/yr

As the platform and team grow, you will establish the standards and patterns future data engineers will follow. KEY RESPONSIBILITIES: * Greenfield Platform Build: Partner with Data Leadership to ...

New

Fracht USA

Senior Data Engineer

Houston, TX · On-site

$91K - $124K/yr

SENIOR DATA ENGINEER The Senior Data Engineer designs, builds, and owns the enterprise data ... DUTIES AND RESPONSIBILITIES Data Platform & Pipeline Engineering * Designs, builds, and maintains ...

Copart, Inc.

Sr. Data Engineer

Dallas, TX · On-site

$113K - $136K/yr

Copart, Inc. a technology leader and the premier online vehicle auction platform globally, with ... The Sr. Data Engineer will be part of the Data & AI Team. The Data & AI Team works very closely ...

AIT Global, Inc.

Senior Data Architect

Irving, TX · On-site

$64.50 - $86.50/hr

We are looking for a Senior Data Architect with strong experience in data architecture, data engineering, data warehousing, and modern Azure data platforms. The ideal candidate will have hands-on ...

Tek Ninjas

Senior Data Engineer

Dallas, TX · On-site

$104K - $142K/yr

The ideal candidate should possess strong expertise in big data technologies, cloud platforms, distributed processing systems, and modern data engineering practices. As a Senior Data Engineer, you ...

Entegris

Senior Data Scientist

Austin, TX · On-site

Senior Data Scientist The Role We are seeking a Senior Data Scientist to lead the design ... Experience with FastAPI, cloud-native application development, and AI platform engineering.

Entegris

Senior Data Scientist

Round Rock, TX

Senior Data Scientist The Role We are seeking a Senior Data Scientist to lead the design ... Experience withFastAPI, cloud-native application development, and AI platform engineering.

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All JobsData Platform Engineer JobsSenior Data Platform Engineer JobsSenior Data Platform Engineer Jobs in Texas

Senior Data Platform Engineer information

What does a senior data platform engineer do?

A Senior Data Platform Engineer is responsible for designing, building, and maintaining large-scale data platforms that support an organization's data analytics and processing needs. They work with various technologies to ensure data is collected, stored, and accessible efficiently and securely. Their role often involves optimizing data pipelines, managing databases, ensuring data quality, and collaborating with data scientists and analysts to deliver reliable data solutions. In addition, they help set best practices and mentor junior engineers on the team.

How does a senior data platform engineer typically collaborate with data scientists and analysts within an organization?

A Senior Data Platform Engineer works closely with data scientists and analysts to understand their data needs and ensure the platform supports efficient data access, processing, and analysis. This often involves designing and implementing data pipelines, optimizing data storage solutions, and ensuring data quality and integrity. Regular communication is essential to align on data requirements, troubleshoot issues, and roll out new platform features that enhance analytical capabilities. Collaboration frequently occurs through agile ceremonies, project meetings, and shared documentation to ensure all stakeholders are aligned and productive.

What are the key skills and qualifications needed to thrive as a senior data platform engineer, and why are they important?

To thrive as a Senior Data Platform Engineer, you need deep expertise in data architecture, database management, ETL design, and programming languages like Python or Java, typically supported by a bachelor's degree in computer science or related field. Familiarity with cloud platforms (such as AWS, Azure, or GCP), big data tools (like Spark or Hadoop), and certifications in relevant technologies are commonly required. Strong problem-solving, collaboration, and communication skills set top performers apart in this role. These competencies are essential for building robust, scalable data systems that support business intelligence and data-driven decision-making.

What is the difference between Senior Data Platform Engineer vs Data Engineer?

AspectSenior Data Platform EngineerData Engineer
CredentialsBachelor's/Master's in CS, Data Science, or related; often certifications in cloud platformsBachelor's in CS, Software Engineering, or related; certifications in data tools are common
Work EnvironmentDesigning, building, and maintaining large-scale data platforms; working with cloud servicesDeveloping data pipelines, ETL processes, and data storage solutions
Industry UsageUsed across tech, finance, healthcare, and retail for managing data infrastructureCommonly employed in similar industries for data processing and integration

The Senior Data Platform Engineer focuses on designing and maintaining scalable data platforms, often with cloud expertise, while Data Engineers primarily develop data pipelines and ETL processes. Both roles require strong technical skills and are vital in data-driven organizations, but the Senior Data Platform Engineer typically has a broader scope and more strategic responsibilities.

What are the most commonly searched types of Data Platform Engineer jobs in Texas?

The most popular types of Data Platform Engineer jobs in Texas are:

What cities in Texas are hiring for Senior Data Platform Engineer jobs?

Cities in Texas with the most Senior Data Platform Engineer job openings:

Senior Data Platform Engineer jobs near you

Snowflake DATA Engineer C2C jobs in Richardson TX

Tech Mirrors

Richardson, TX • On-site

$100 - $130/hr

Other

Posted 2 days ago

New

Job description

Snowflake Data Engineer

Location: Richardson, TX (onsite)
Contract

We are looking for a Senior Data Platform Engineer candidate who will design and operate data pipelines that connect heterogeneous source systems, normalize data into consumption‑ready models in Snowflake, and build AI‑powered agents that surface intelligence across the platform.

Core Responsibilities
  • Snowflake engineering: design schemas, write performant SQL, manage roles, warehouse sizing, and implement change management practices.
  • ETL/ELT development: build and maintain pipelines that ingest from diverse sources (APIs, databases, event streams) and normalize data for BI and downstream consumers.
  • AI agent development: leverage Snowflake Cortex and AI agent frameworks to build intelligent data products and automate analytical workflows.
  • Backend API connectivity: develop backend integrations with internal and third‑party systems via REST APIs and backend services.
Required Skills
  • Snowflake hands‑on experience building and optimizing data models, writing advanced SQL (PIVOT, GROUPING SETS, ROLLUP/CUBE), and managing Snowflake environments in production.
  • Multisource integration: proven ability to connect and ingest data from heterogeneous sources including relational databases, REST APIs, SaaS platforms, and event streams.
  • ETL/ELT design: experience designing normalized schemas and transformation pipelines that produce clean, consumption‑ready data models using snowflake‑schema dimensional modeling.
  • Python: strong proficiency for data engineering tasks, pipeline orchestration, data transformation, API clients, and scripting automation.
  • AI agents within Snowflake: familiarity with Snowflake Cortex LLM functions and agent‑based patterns for building intelligent, data‑driven workflows inside the Snowflake ecosystem.
  • Backend integration patterns: practical experience building backend services and integrations using Python, REST APIs, and related tooling (authentication, pagination, error handling, retry logic).
Additional Skills
  • PostgreSQL relational databases: working knowledge of PostgreSQL or equivalent RDBMS, including query optimization, indexing, and schema design patterns.
  • Go (Golang): experience building backend services or microservices in Go is a strong differentiator.
  • Cloud data infrastructure: familiarity with Azure or AWS data services (e.g., Azure Data Factory, Event Hubs, S3 as source or orchestration layers).
  • Data observability and testing: experience with data quality frameworks (dbt tests) or observability tooling (Great Expectations, Monte Carlo, etc.).

You’re a self‑directed engineer who thrives at the intersection of data engineering and platform thinking, can navigate ambiguous requirements, design for scale, and communicate clearly across engineering and product stakeholders. You care about data quality, documentation, and building systems that other teams love to consume.

Skills
  • Mandatory Skills: ETL concepts, Python for data, Snowflake.
  • Good to Have Skills: AWS S3, Azure Data Factory, PostgreSQL, Python – Data Science, Snowflake AI/ML.
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