Data Analysis Jobs in Austin, TX

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Looking for Data Analysis jobs in Austin, TX? Browse our curated listings with transparent salary information to find the perfect Data Analysis position in the Austin, TX area.

SRAM Circuit Design Engineer

Company: Apple

Location: Austin, TX

Posted Feb 03, 2025

Sales Associate

Company:

Location: Midland, TX

Posted Feb 03, 2025

Pedi Home Health Nursing - LVN/RN

Company:

Location: Tyler, TX

Posted Feb 03, 2025

Electrician - Hourly

Company:

Location: Montgomery, TX

Posted Feb 03, 2025

Solutions Consultant

Company: Palo Alto Networks

Location: Dallas-Fort Worth, TX

Posted Feb 03, 2025

Palo Alto Networks is a cybersecurity company committed to protecting the digital way of life. They value innovation, collaboration, and disruption. The Solutions Consultant role involves providing technical leadership, defining solutions for customers' security transformation, and meeting sales quotas. The company offers competitive compensation, benefits, and a supportive work environment. They are an equal opportunity employer committed to diversity and inclusion.

Pediatric Home Heath Nurse

Company:

Location: Temple, TX

Posted Feb 03, 2025

Senior Software Engineer (Hybrid)

Company: Motorola Solutions

Location: Dallas-Fort Worth, TX

Posted Feb 03, 2025

Motorola Solutions is seeking a software engineer for their Cloud Platform Engineering team. The role involves designing and implementing CICD pipelines, developing and operating common platform services, ensuring high availability and security, and providing monitoring and support. The ideal candidate will have experience with Elasticsearch, Prometheus, Kubernetes, and cloud platforms like AWS, Azure, and GCP. They should be comfortable with Java, Spring, Golang, or Python, and have experience with modern development operations tooling. The position requires on-call work and US citizenship due to security clearance requirements. Benefits include incentive bonus plans, medical and dental benefits, 401K with company match, and more.

Private Duty RN

Company:

Location: Lubbock, TX

Posted Feb 03, 2025

RN Clinical Supervisor

Company:

Location: Temple, TX

Posted Feb 03, 2025

Frequently Asked Questions

What are typical salary ranges for Data Analysis roles by seniority?
Entry‑level Data Analysts earn $65k–$85k, mid‑level $85k–$115k, senior $115k–$150k, and analytics leaders or managers range $140k–$190k. These figures reflect U.S. averages and vary by region and industry.
Which technical skills and certifications are most valuable for Data Analysis professionals?
Strong proficiency in <strong>SQL</strong>, <strong>Python</strong>, <strong>R</strong>, and spreadsheet modeling is essential. Building dashboards in <strong>Tableau</strong> or <strong>Power BI</strong>, working with cloud warehouses like <strong>Snowflake</strong> or <strong>BigQuery</strong>, and knowledge of statistical testing are core. Certifications such as Certified Analytics Professional (CAP), Google Data Analytics Professional Certificate, Microsoft Certified: Data Analyst Associate, Tableau Desktop Specialist, and AWS Certified Data Analytics – Specialty boost credibility.
Is remote work common for Data Analysis positions?
Yes—over 70% of listings on jobtransparency.com offer full‑remote or hybrid models. Remote analysts frequently use cloud data platforms (Snowflake, BigQuery), version control (Git), and collaboration tools like Slack and Microsoft Teams to maintain data integrity and stakeholder communication.
What career progression paths are available for Data Analysis talent?
Typical growth moves from Junior Analyst to Senior Analyst, then to Analytics Lead or Manager, and ultimately to Director of Analytics or VP of Data. Specializations such as predictive modeling, data engineering, or product analytics create additional advancement opportunities, especially when coupled with continuous learning and certifications.
What industry trends are shaping the future of Data Analysis?
Key trends include real‑time stream analytics, AI‑augmented analytics that automate insights, growing adoption of cloud data lakes and lakehouses, heightened focus on data governance, privacy compliance, and the need for explainable AI dashboards that blend statistical rigor with narrative storytelling.

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