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Freelance Data Platform Engineer Jobs in Texas (NOW HIRING)

Wise Skulls

Data Platform Engineer

Austin, TX · On-site

$113K - $136K/yr

Data Platform Engineer Location: Austin, TX or Sunnyvale, CA (Hybrid) Duration: 6 months (possibility of extension) Implementation Partner: Infosys End Client: To be disclosed JD: Job Summary We are ...

MyHR Partner, Inc

Data Platform Engineer

Austin, TX · On-site

$135K - $155K/yr

Description Your Ideal Data Platform Engineer Job * Are you passionate about powering the data behind AI-driven solutions? * Do you thrive on solving large-scale data challenges across structured ...

myHR Partner

Data Platform Engineer

Austin, TX · On-site +1

$135K - $155K/yr

Your Ideal Data Platform Engineer Job * Are you passionate about powering the data behind AI-driven solutions? * Do you thrive on solving large-scale data challenges across structured, semi ...

Prophecy Technologies

AWS Data Platform Engineer

Dallas, TX · On-site

$113K - $136K/yr

Hi We are seeking an experienced AWS Data Platform Engineer to design, build, and operate enterprise-grade data pipelines across both on-premises and AWS cloud environments. This role will be ...

Eitacies Inc

Senior Data Platform Engineer

Austin, TX · On-site

$105K - $143K/yr

Benefits: * 401(k) Senior Data Platform Engineer Onsite Austin, TX We are hiring a Senior Data Platform Engineer for an onsite role in Austin, TX This role requires strong hands-on experience ...

The Bronx

Sr. Data Platform Engineer

Addison, TX · On-site

$135 - $145/hr

POSITION OVERVIEW The Senior Data Platform Engineer will build, operate, and secure a modern Snowflake data platform using a medallion architecture. Working closely with the Data Architect, this ...

New

Wise Skulls Corp.

W2 Role : Data Platform Engineer

Manor, TX · On-site

$123K - $148K/yr

Austin, TX or Sunnyvale, CA (Hybrid) Job Summary We are seeking an experienced Data Platform Engineer to architect, build, and operate our cloud-based data lakehouse platform. The role is responsible ...

Honor

Staff Data Platform Engineer

Austin, TX · Remote

The Opportunity We're looking for a Staff Data Engineer to help shape the future of Honor's data platform. This role is focused on building the foundational data platform that powers analytics ...

Handraise, Inc.

Senior Data Platform Engineer

Austin, TX · On-site

$140 - $210/hr

We are seeking a highly skilled Senior Data Platform Engineer to help us build the future of AI brand perception intelligence. Founded in 2023, Handraise is an AI-native narrative intelligence ...

New

Eitacies Inc

Sr GCP Data Engineer

Austin, TX · On-site

$114K - $137K/yr

Benefits: * 401(k) Senior Data Platform Engineer Onsite Austin, TX We are hiring a Senior Data Platform Engineer for an onsite role in Phoenix, AZ. This role requires strong hands-on experience ...

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

Freelance Data Platform Engineer information

What is a freelance data platform engineer?

A Freelance Data Platform Engineer is a professional who designs, builds, and maintains data infrastructure and platforms on a project or contract basis, rather than as a full-time employee. They work with clients to develop scalable and efficient data solutions, such as data warehouses, ETL pipelines, and cloud-based data systems. Their responsibilities often include integrating various data sources, ensuring data quality, and optimizing data workflows to support analytics and business intelligence. Freelance Data Platform Engineers typically have expertise in databases, cloud services, programming, and data architecture. They offer flexibility and specialized skills to organizations that need temporary or project-based support.

What are the key skills and qualifications needed to thrive as a freelance data platform engineer?

To thrive as a Freelance Data Platform Engineer, you need strong skills in data architecture, ETL processes, and cloud platform management, typically supported by a degree in computer science or a related field. Familiarity with tools like SQL, Python, Spark, AWS, Azure, and certifications such as AWS Certified Data Analytics or Google Cloud Data Engineer are highly valuable. Effective client communication, problem-solving, and project management skills help you stand out, especially when coordinating independently with multiple stakeholders. These competencies ensure you can design scalable solutions, deliver projects efficiently, and build strong client relationships in a dynamic freelance environment.

How do freelance data platform engineers typically manage collaboration with clients and remote teams?

Freelance Data Platform Engineers often collaborate with clients and distributed teams using project management tools, version control systems, and regular virtual meetings. Clear communication is essential for aligning on data requirements, setting expectations, and providing progress updates. It's common to work asynchronously, so documenting work and maintaining transparent workflows help ensure smooth handoffs. Building trust and reliability is key to fostering long-term client relationships in a freelance setting.

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

AspectFreelance Data Platform EngineerData Engineer
CredentialsRelevant certifications (e.g., AWS, GCP, Azure), technical skillsSimilar certifications, technical skills, often full-time roles
Work EnvironmentIndependent, project-based, remote or on-siteFull-time, in-house or remote
Employer & Industry UsageFreelance platforms, consulting firms, startupsTech companies, finance, healthcare, large enterprises
Search & Comparison IntentYes, for freelance opportunities or project-based workYes, for full-time or contract roles

In summary, Freelance Data Platform Engineers typically work independently on short-term projects, requiring similar skills and certifications as Data Engineers but with a focus on flexibility and client-based work. Data Engineers often work full-time within organizations, focusing on building and maintaining data infrastructure.

How much do freelance data platform engineers make?

Freelance data platform engineers typically earn between $50 and $150 per hour, depending on experience, skills, and project complexity. Experienced professionals with expertise in cloud platforms, data pipelines, and tools like Apache Spark or Kafka tend to command higher rates. Annual earnings vary widely based on workload and client base, often ranging from $80,000 to over $200,000 for full-time equivalent work.

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 are popular job titles related to Freelance Data Platform Engineer jobs in Texas?

For Freelance Data Platform Engineer jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Freelance Data Platform Engineer jobs in Texas look for?

The top searched job categories for Freelance Data Platform Engineer jobs in Texas are:

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

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

Freelance Data Platform Engineer jobs near you

Data Platform Engineer

Wise Skulls

Austin, TX • On-site

$113K - $136K/yr

Contractor

Posted 10 days ago

Job description

Title: Data Platform Engineer
Location: Austin, TX or Sunnyvale, CA (Hybrid)
Duration: 6 months (possibility of extension)
Implementation Partner: Infosys
End Client: To be disclosed
JD:
Job Summary
We are seeking an experienced Data Platform Engineer to architect, build, and operate our cloud-based data lakehouse platform. The role is responsible for developing scalable
data infrastructure and processing pipelines built on open table formats, distributed query and compute engines, and containerized cloud infrastructure - enabling analysts, data
scientists, and downstream applications to access reliable, high-performance data at scale. The ideal candidate combines deep distributed-systems and data engineering expertise with
strong software engineering practices and a passion for building robust, efficient platforms.
Key Responsibilities
Lakehouse Architecture (Apache Iceberg)
- Architect, implement, and maintain the data lakehouse using Apache Iceberg table formats.
- Manage table lifecycle including partitioning, schema evolution, snapshot and metadata management, and compaction.
- Optimize table layout and file sizing for query performance, storage efficiency, and cost.
- Implement data governance, time-travel, and ACID transaction patterns across the lakehouse.
Distributed Query & Compute (Trino & Spark)
- Deploy, tune, and operate Trino clusters for interactive and federated analytics; manage connectors, catalogs, and resource groups.
- Build and optimize large-scale batch and streaming data processing with Apache Spark.
- Troubleshoot query plans, job performance, spills, and shuffle bottlenecks across distributed workloads.
- Balance capacity, concurrency, and cost across query and compute engines.
Data Engineering (Scala & Python)
- Develop scalable data pipelines, frameworks, and services in Scala and Python.
- Build reusable ingestion, transformation, and data-quality libraries for batch and streaming.
- Write clean, well-tested, performant code following software engineering best practices.
- Integrate pipelines with the Iceberg lakehouse and Trino/Spark processing layers.
Cloud & Kubernetes Infrastructure
- Design and operate data platform components on Kubernetes (EKS, AKS, GKE, or self-managed).
- Build and manage containerized workloads, Helm charts, and autoscaling for data services.
- Provision and manage cloud infrastructure (AWS, Azure, or GCP), including object storage and compute.
- Implement infrastructure as code, CI/CD, monitoring, and observability for the platform.
Platform Reliability & Collaboration
- Ensure the reliability, scalability, and security of the data platform across environments.
- Automate deployment, testing, and operational workflows to eliminate toil.
- Partner with data consumers to understand requirements and improve data accessibility.
- Mentor engineers and promote best practices in data and platform engineering.

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