Data Analytics Engineer

Healthtronics•Austin, TX

About The Position

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.

Requirements

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.

Nice To Haves

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.

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.