Data Analytics Engineer

Healthtronics; Austin (TX); On-site; USD 95,000 - 125,000; Full time

Job summary

Healthtronics in Austin, TX is seeking a Data Analytics Engineer to design, build, and maintain scalable data pipelines and analytics platforms that enable data-driven decision making across the organization. This role bridges data engineering and business intelligence by turning raw data into trusted, accessible insights.

You will collaborate with stakeholders, develop KPIs, dashboards, and reporting frameworks, and ensure data governance and quality across enterprise data assets to support

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, Mathematics, or a related field.
• 3+ years of experience in data engineering, analytics engineering, business intelligence, or related roles.
• Strong SQL development and database management skills.
• Experience with data warehouse technologies and cloud data platforms.
• Proficiency in Python, SQL, or other data processing languages.
• Experience with BI and visualization tools such as Sigma, Tableau, or similar platforms.
• Knowledge of ETL/ELT frameworks and data integration methodologies.

Responsibilities

• Design, develop, and maintain ETL/ELT processes for ingesting, transforming, and integrating data from multiple sources.
• Build and optimize data pipelines to ensure data quality, reliability, and performance.
• Develop and maintain enterprise data models, data warehouses, and data marts.
• Monitor and troubleshoot data workflows and resolve data-related issues.
• Create and maintain dashboards, reports, and self-service analytics solutions using modern BI tools.
• Translate business requirements into scalable analytical solutions.
• Develop KPIs, metrics, and reporting frameworks to measure business performance.
• Support ad hoc data analysis and reporting requests.
• Implement data quality controls and validation processes.
• Ensure compliance with organizational data governance policies and security standards.
• Maintain data dictionaries, metadata, and documentation.
• Promote best practices for data management and analytics.
• Partner with business stakeholders to understand reporting and analytical needs.
• Work closely with application teams and business process owners to improve data accessibility and usability.
• Provide technical guidance and mentoring to analysts and other team members.
• Present analytical findings and recommendations to leadership.

Skills

SQL development

Python

BI tools

Education

Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, Mathematics, or related field

Tools

Azure Data Factory

Tableau

Databricks

Snowflake

Job description

Job title: Data Analytics Engineer

Location: Austin, TX, US

Job Type: Technical

Category: Full Time Regular

Requisition ID: 2314

SUMMARY OF PURPOSE

The Data Analytics Engineer is responsible for designing, building, and maintaining scalable data pipelines, analytics platforms, and reporting solutions that enable data-driven decision making across the organization. This role bridges the gap between data engineering and business intelligence by transforming raw data into trusted, accessible, and actionable insights. The Data Analytics Engineer collaborates closely with business stakeholders, data analysts, IT teams, and leadership to deliver high-quality data solutions that support strategic objectives.

ESSENTIAL FUNCTIONS

Data Engineering & Integration

• Design, develop, and maintain ETL/ELT processes for ingesting,transforming, and integrating data from multiple sources.
• Build and optimize data pipelines to ensure data quality, reliability, and performance.
• Develop and maintain enterprise data models, data warehouses, and data marts.
• Monitor and troubleshoot data workflows and resolve data-related issues.

Analytics & Reporting

• Create and maintain dashboards, reports, and self-service analytics solutions using modern BI tools.
• Translate business requirements into scalable analytical solutions.
• Develop KPIs, metrics, and reporting frameworks to measure business performance.
• Support ad hoc data analysis and reporting requests.

Data Governance & Quality

• Implement data quality controls and validation processes.
• Ensure compliance with organizational data governance policies and security standards.
• Maintain data dictionaries, metadata, and documentation.
• Promote best practices for data management and analytics.

Collaboration & Business Partnership

• Partner with business stakeholders to understand reporting and analytical needs.
• Work closely with application teams and business process owners to improve data accessibility and usability.
• Provide technical guidance and mentoring to analysts and other team members.
• Present analytical findings and recommendations to leadership.

POSITION REQUIREMENTS - REQUIRED QUALIFICATIONS:

• Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, Mathematics, or a related field.
• 3+ years of experience in data engineering, analytics engineering, business intelligence, or related roles.
• Strong SQL development and database management skills.
• Experience with data warehouse technologies and cloud data platforms.
• Proficiency in Python, SQL, or other data processing languages.
• Experience with BI and visualization tools such as Sigma, Tableau, or similar platforms.
• Knowledge of ETL/ELT frameworks and data integration methodologies.

PREFERRED QUALIFICATIONS:

• Experience with Azure Data Factory, Microsoft Fabric, Synapse Analytics, Databricks, or Snowflake.
• Understanding of data governance and master data management practices.
• Experience working in Agile environments.
• Relevant certifications in Azure, Microsoft Fabric, Power BI, or data engineering technologies.

KEY COMPETENCIES:

• Analytical thinking and problem-solving
• Data modeling and architecture
• Stakeholder communication
• Process improvement
• Attention to detail
• Project management and prioritization
• Collaboration and teamwork

SUCCESS MEASURES:

• Delivery of reliable and scalable analytics solutions.
• Improvement in data quality and reporting accuracy.
• Reduction in manual reporting efforts.
• Increased adoption of self-service analytics capabilities.
• Timely delivery of data and analytics initiatives aligned with business goals.

PHI ACCESS

• This position requires access to PHI due to reporting and data content