Analytics Engineer
Job Summary
We are seeking an Analytics Engineer to join our Data & Analytics team and play a key role in designing developing and maintaining our enterprise data platform. This position combines strong SQL development data engineering data warehousing semantic modeling and analytics expertise to ensure reliable scalable and high-quality data is available to business users and analytics teams.
The Analytics Engineer will support the Sr. Manager Data & Analytics by executing the hands-on technical work required to maintain optimize and continuously evolve the enterprise data platform. The ideal candidate is comfortable working across the data stackfrom ETL/ELT pipelines and data warehouses to semantic models and certified datasetsand has a strong focus on data quality performance reliability and maintainability.
- Design develop and maintain enterprise data warehouse structures tables views and related data assets
- Develop efficient and scalable SQL queries stored procedures transformations and data models
- Build and maintain ETL/ELT processes that integrate data from multiple enterprise sources
- Develop and support data pipelines using Azure Data Factory
- Monitor data pipelines and proactively identify troubleshoot and resolve failures and data processing issues
- Implement appropriate error handling logging alerting and recovery processes
- Support the ongoing enhancement and evolution of the enterprise data platform
- Design and maintain semantic models that enable consistent trusted and user-friendly access to enterprise data
- Develop and maintain certified datasets for reporting analytics and business intelligence
- Translate business and analytical requirements into scalable data models and technical solutions
- Establish consistent definitions relationships calculations and business logic across analytical datasets
- Partner with data analysts BI developers and business stakeholders to ensure data solutions meet reporting and analytical needs
- Develop and automate data quality checks validation processes and monitoring capabilities
- Identify data quality issues and work with appropriate teams to determine root causes and implement solutions
- Optimize SQL queries data models and pipelines to improve performance and scalability
- Perform platform performance tuning and identify opportunities to improve reliability and efficiency
- Monitor overall data platform health and contribute to performance and capacity improvements
- Create and maintain technical documentation for data models pipelines transformations processes and data definitions
- Establish and follow standards for SQL development data modeling pipeline development and data quality
- Contribute to data engineering best practices development standards and platform governance
- Participate in code reviews and provide recommendations to improve the quality maintainability and performance of data solutions
- Bachelors degree in Computer Science Information Systems Data Analytics Engineering or a related field or equivalent professional experience
- 3 years of experience in analytics engineering data engineering business intelligence data warehousing or a related discipline
- Strong hands-on experience with SQL and relational databases
- Experience designing and developing data warehouse solutions
- Experience developing and supporting ETL/ELT pipelines
- Experience with Azure Data Factory or a similar cloud-based data integration platform
- Strong understanding of data modeling including dimensional modeling and analytical data structures
- Experience developing semantic models and curated/certified datasets
- Experience troubleshooting data pipelines identifying root causes and resolving data issues
- Understanding of data quality validation monitoring and automated testing concepts
- Strong analytical and problem-solving skills
- Ability to document technical solutions clearly and effectively
- Experience working within the Microsoft Azure data and analytics ecosystem
- Experience with Power BI or similar business intelligence platforms
- Experience with Azure SQL SQL Server Azure Synapse Analytics Microsoft Fabric or similar data platforms
- Experience with source control and collaborative development practices such as Git
- Experience with CI/CD and deployment processes for data solutions
- Knowledge of data governance metadata management and enterprise data standards
- Experience optimizing large-scale SQL queries and data warehouse workloads
- Familiarity with automated data quality and pipeline monitoring frameworks
- Experience working in an enterprise environment with multiple data sources and business domains
Required Skills:
3 years of experience in analytics engineering data engineering business intelligence data warehousing or a related discipline Strong hands-on experience with SQL and relational databases Experience designing and developing data warehouse solutions Experience developing and supporting ETL/ELT pipelines Experience with Azure Data Factory or a similar cloud-based data integration platform Strong understanding of data modeling including dimensional modeling and analytical data structures Experience developing semantic models and curated/certified datasets Experience troubleshooting data pipelines identifying root causes and resolving data issues Understanding of data quality validation monitoring and automated testing concepts Strong analytical and problem-solving skills Ability to document technical solutions clearly and effectively PREFERRED QUALIFICATIONS Experience working within the Microsoft Azure data and analytics ecosystem Experience with Power BI or similar business intelligence platforms Experience with Azure SQL SQL Server Azure Synapse Analytics Microsoft Fabric or similar data platforms Experience with source control and collaborative development practices such as Git Experience with CI/CD and deployment processes for data solutions Knowledge of data governance metadata management and enterprise data standards Experience optimizing large-scale SQL queries and data warehouse workloads Familiarity with automated data quality and pipeline monitoring frameworks Experience working in an enterprise environment with multiple data sources and business domains
Required Education:
Bachelors degree in Computer Science Information Systems Data Analytics Engineering or a related field or equivalent professional experience