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Full Time Data Engineering Jobs in Austin, TX (NOW HIRING)

Senior Data Scientist, Applied ML

Austin, TX · On-site +1

$154K - $200K/yr

You'll build the preprocessing and feature engineering pipelines your own models depend on, and you ... S.-Based Benefits + Perks (for Full Time Employees): At SpyCloud, we are committed to working ...

Data Engineer

Austin, TX · On-site

$113K - $136K/yr

Data Engineer Employment Type: Full-Time, Mid-level Department: Business Intelligence CGS is seeking a passionate and driven Data Engineer to support a rapidly growing Data Analytics and Business ...

Snowflake Data Engineer

Austin, TX · On-site

$113K - $136K/yr

Role: Sr. Snowflake Data Engineer/only W2 Location ... Austin, TX Onsite position Fulltime Position TCS/Apple JD: * Expert level fluency with Snowflake ...

Sr. Data Engineer

Austin, TX · On-site

$113K - $136K/yr

Role: Sr. Snowflake Data Engineer Location ... Austin, TX - Fulltime Position Minimum Qualifications: * Expert level fluency with Snowflake, SQL ...

RWE Americas, LLC To start as soon as possible, full time, permanent Functional area: IT / Digital ... Build and lead a high-performing team of product managers, data engineers, data architects ...

RWE Americas, LLC To start as soon as possible, full time, permanent Functional area: IT / Digital ... Build and lead a high-performing team of product managers, data engineers, data architects ...

Pricing Data Engineer

Austin, TX · On-site

$110K - $169K/yr

The Pricing Data Engineer builds and maintains the data infrastructure and tools that enable ... work. Full time positions are eligible for a discretionary bonus and a comprehensive benefits ...

Showing results 41-60

Full Time Data Engineering information

See Austin, TX salary details

$44.1K

$128.6K

$175.9K

How much do full time data engineering jobs pay per year?

As of Sep 3, 2026, the average yearly pay for full time data engineering in Austin, TX is $128,576.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $136,300.00 per year, depending on experience, location, and employer.

What is a full time data engineer?

Full time data engineering jobs involve building, managing, and optimizing data pipelines and infrastructure to collect, process, and store large volumes of data for organizations. Data engineers work with technologies like SQL, Python, cloud platforms, and big data tools to ensure data is reliable and accessible for analytics and business decision-making. These roles typically require strong programming skills, knowledge of database systems, and experience with data modeling and ETL (Extract, Transform, Load) processes. Full time positions generally offer benefits and require a standard workweek commitment, often in tech, finance, healthcare, or other data-driven industries.

What are the key skills and qualifications needed to thrive as a full time data engineer?

To thrive as a Full Time Data Engineer, you need strong programming skills (such as Python or Java), proficiency in SQL, and a solid understanding of data modeling and ETL processes, usually supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop or Spark), cloud platforms (such as AWS or Azure), and relevant certifications (e.g., Google Cloud Data Engineer) is highly valuable. Excellent problem-solving, communication, and teamwork abilities distinguish top performers in this role. These skills ensure efficient data infrastructure development, reliable data pipelines, and effective collaboration with cross-functional teams to support business objectives.

What are some common challenges faced by full time data engineers, and how can they be addressed?

Full-time data engineers often encounter challenges such as integrating data from diverse sources, ensuring data quality, and optimizing data pipelines for scalability and performance. These issues can be addressed by adopting robust ETL (Extract, Transform, Load) frameworks, implementing automated data validation tests, and collaborating closely with data analysts and software engineers to align on data requirements. Staying updated with the latest cloud technologies and best practices in data architecture also helps in overcoming these challenges and maintaining efficient, reliable data systems.

What is the difference between Full Time Data Engineering vs Part Time Data Engineering?

AspectFull Time Data EngineeringPart Time Data Engineering
Work HoursTypically 40 hours/weekLess than 20 hours/week
CredentialsRelevant degrees, certifications like AWS, GCP, or AzureSame as full-time, but often less emphasis on certifications
Work EnvironmentFull-time employment, often in corporate or tech firmsFreelance or contract basis, flexible locations
Job ResponsibilitiesDesigning, building, maintaining data pipelinesSupporting existing pipelines, smaller projects

Full Time Data Engineering involves a standard 40-hour workweek with comprehensive responsibilities in designing and maintaining data systems. Part Time Data Engineering offers flexible hours, often focusing on specific tasks or projects. Both roles require relevant technical skills and certifications, but full-time positions typically demand more extensive experience and commitment.

Are data engineers still in demand?

Data engineers are currently in high demand due to the increasing reliance on data-driven decision making and the growth of big data technologies. Organizations seek professionals skilled in tools like SQL, Python, and cloud platforms to build and maintain data pipelines, making this a stable and growing career field.

What are the most commonly searched types of Data Engineering jobs in Austin, TX?

The most popular types of Data Engineering jobs in Austin, TX are:

What cities near Austin, TX are hiring for Full Time Data Engineering jobs?

Cities near Austin, TX with the most Full Time Data Engineering job openings:

Software Engineering Manager, Data Solutions & Initiatives

Apple

Austin, TX • On-site

Full-time

Re-posted 22 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 680 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers


Job description

The people here at Apple don't just create products - they create the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it.
We operate in a startup-like environment within Apple's Worldwide Sales organization, where Data Solutions & Initiatives (DSI) drives innovation through product design, engineering, and portfolio management for our internal Apple customers. We move quickly, experiment boldly, and expect our team members to take full ownership of what they deliver.
Description
We are seeking an experienced Software Engineering Manager to lead a high-performing, full-stack engineering team building the internal platforms, data systems, and increasingly AI-driven applications that power critical business decisions across Apple's global sales organization. In this senior leadership role, you will establish operational objectives, drive technical strategy, and deliver high-quality, scalable solutions across a complex and fast-moving environment. You will manage a blended team of full-time engineers and variable workforce - including tech leads who provide functional oversight within their areas - while regularly engaging with senior and executive leadership across multiple functional areas. Your decisions will directly shape the pace and direction of our technology roadmap, and your ability to influence across teams and organizations will be as important as your technical depth.
Minimum Qualifications
12+ years of professional software engineering experience, with hands-on expertise across full-stack development (frontend, backend, and data layers)
4+ years of engineering management experience, with demonstrated success leading and growing teams of 8 or more engineers across multiple workstreams or functional areas
Track record of leading your team's adoption of AI-assisted development practices - setting clear standards for when and how to leverage AI effectively while maintaining engineering rigor
Experience owning and managing team budgets, headcount plans, and resource allocation across both FTE and variable/contractor workforce
Proven track record of establishing operational objectives, setting performance expectations, and holding teams accountable to schedules and quality standards
Deep, practical knowledge of distributed systems design, RESTful APIs, and service-oriented architectures
Experience with relational and NoSQL databases (e.g., PostgreSQL or equivalent)
Strong proficiency in at least two modern programming languages (e.g., Python, JavaScript/TypeScript, Go or equivalent)
Track record of delivering high-quality software in an agile environment using CI/CD, automated testing, and source code management best practices
Demonstrated ability to engage regularly with senior and executive leadership - translating technical strategy into business impact and navigating sensitive cross-functional situations with diplomacy and poise
Experience collaborating with multi-functional teams across product, design, data, and business stakeholders
Bachelor's degree in Computer Science, Computer Engineering or a related technical field, or equivalent practical experience
Preferred Qualifications
Experience building or managing internal tooling, business platforms, or enterprise-grade applications at scale
Familiarity with cloud-native architecture and modern infrastructure practices (e.g., Kubernetes, containerization, observability stacks, cloud platforms)
Background in data engineering or managing teams building data pipelines, analytics platforms, or reporting infrastructure
Experience working in a high-growth or startup-like environment within a large enterprise organization
Experience building or integrating AI/ML-powered features into production applications (e.g., predictive analytics, intelligent automation, LLM-based tooling)
Track record of leading platform modernization efforts - such as service migrations, API standardization, or developer experience improvements
Experience developing or influencing engineering policies and operational standards with broad organizational impact
Demonstrated ability to influence technical direction and build alignment across peer engineering teams and divisions without formal authority
Passion for building inclusive engineering culture, cultivating psychological safety, and investing in the development of every team member

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976