Analytics Engineer
Troy, Oakland County, Michigan, 48083, USA
Listed on 2026-10-02
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IT/Tech
Data Engineering, Data Warehousing
Analytics Engineer
Full Time Remote
We are looking for an experienced Analytics Engineer to join our team and help build the data infrastructure that powers analytics and decision making across the organization
In this role youll design develop and optimize modern data platforms pipelines and data models that make trusted high quality information accessible to teams across the business
Youll work closely with both technical teams and business stakeholders to understand data needs solve complex problems and create scalable solutions
The ideal candidate is a hands on data professional with strong SQL and data engineering experience a solid understanding of modern cloud data platforms and a passion for building reliable well governed data environments
What You’ll Do- Design develop and maintain scalable ETLELT pipelines and data integration processes
- Build and optimize data models that support enterprise reporting analytics and self service BI
- Work with platforms such as Microsoft Fabric Snowflake Azure Data Factory and other enterprise data technologies
- Ensure data is accurate reliable secure and accessible through strong data quality and governance practices
- Monitor data pipelines and platforms to identify performance reliability and scalability issues
- Troubleshoot data issues identify root causes and implement effective solutions
- Partner with business stakeholders Analytics Developers and technical teams to translate business requirements into effective data solutions
- Support enterprise analytics initiatives by providing clean structured and trusted data
- Automate data workflows and identify opportunities to improve efficiency and scalability
- Maintain technical documentation data standards and best practices
- Support compliance requirements including HIPAA PCI data privacy and enterprise security standards
- Stay current with emerging data technologies architectures and engineering best practices
- 3 years of experience designing developing and maintaining data pipelines data integration processes and/or enterprise data platforms
- Strong proficiency in SQL and experience with database management and optimization
- Experience with ETLELT development data modeling and data integration
- Understanding of data engineering principles and modern analytics architectures
- Experience working with relational and/or cloud based data platforms
- Strong analytical and problem solving skills with the ability to troubleshoot complex data issues
- Ability to collaborate effectively with both technical and non technical stakeholders
- Strong communication skills and the ability to explain technical concepts to diverse audiences
- Bachelors degree in Computer Science Information Systems Data Engineering Software Engineering Mathematics or a related technical field preferred or equivalent experience
- Experience with Microsoft Fabric Azure Data Factory Azure Synapse Snowflake or comparable cloud data platforms
- Experience designing and maintaining enterprise scale ETLELT pipelines
- Knowledge of modern data architecture concepts including Lakehouse data warehouse and medallion architecture
- Experience with data quality monitoring metadata management and data governance
- Familiarity with Python Spark or other scripting programming languages used for data processing and automation
- Experience with Git CICD and Dev Ops methodologies
- Experience working in healthcare or another highly regulated industry
- Understanding of HIPAA data privacy security and compliance requirements
This is an opportunity to play a key role in building and evolving our organizations data environment Youll have the opportunity to work across teams solve meaningful business problems and help establish data solutions that support smarter more efficient decision making If you enjoy turning complex data challenges into scalable reliable solutions we’d love to hear from you
Smile Partners USA is an Equal Opportunity Employer
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