Note: The job is a remote job and is open to candidates in USA. Pivotal Talent Search is seeking a Senior Data Analytics Engineer to design, build, and scale enterprise Data & Analytics solutions. The role focuses on ETL development, data engineering, business intelligence, Power BI, data modeling, and collaboration with Data Scientists and business stakeholders to deliver scalable and reliable data solutions.
Responsibilities
- Design, engineer, and implement scalable Data & Analytics solutions that support key business initiatives
- Build and enhance ETL processes that ingest, transform, and integrate data from a variety of internal and third-party sources
- Develop reliable data pipelines and resolve complex technical and data-related issues
- Contribute to the continued growth of the enterprise Data Catalog through the ingestion and integration of new data sources
- Define and implement data standards that improve consistency, quality, accessibility, and business decision-making
- Support the continued evolution of enterprise schemas and data models as new data sources and business requirements emerge
- Design and develop Power BI datasets, semantic models, dashboards, and reporting solutions
- Build sophisticated business logic and calculations using DAX
- Develop and enhance dimensional data models and data warehouse structures that support enterprise analytics and reporting
- Translate complex data and business requirements into scalable Business Intelligence solutions
- Ensure data models and reporting solutions provide accurate, meaningful, and actionable information to business stakeholders
- Contribute independently to Data & Analytics engineering initiatives within an Agile/Scrum environment with minimal supervision
- Take ownership of assigned work from requirements and solution design through development, testing, implementation, and support
- Participate in peer reviews and cross-team engineering communities to share ideas, strengthen standards, and continuously improve development practices
- Maintain comprehensive technical documentation around data solutions, processes, architecture, and key decisions
- Identify opportunities to improve automation, performance, scalability, and overall engineering efficiency
- Partner with Data Scientists to enhance the scalability of machine learning solutions during model training and deployment
- Build and support the data pipelines and engineering capabilities required for advanced analytics and Data Science initiatives
- Collaborate across Data Engineering, Business Intelligence, Analytics, and Data Science to develop integrated enterprise solutions
- Translate business needs into technical solutions while communicating effectively with both technical and non-technical stakeholders
Skills
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field
- 5+ years of progressive Data & Analytics engineering experience
- Strong hands-on Data Engineering experience designing, developing, and supporting ETL solutions using industry-standard tools
- Strong Business Intelligence engineering experience using Power BI or comparable enterprise BI platforms
- Advanced SQL programming skills with the ability to work with complex enterprise datasets
- Strong knowledge of data warehousing, Business Intelligence, data integration, and enterprise analytics environments
- Experience designing, building, troubleshooting, and supporting end-to-end data solutions
- Ability to independently own technical work while contributing effectively within an Agile/Scrum environment
- Strong analytical and problem-solving skills with the ability to identify root causes and drive technical issues through resolution
- Strong communication and collaboration skills with the ability to work across technical, analytics, and business teams
- Advanced Power BI experience, including dataset design and complex DAX development
- Programming experience with Python or Scala within a Data Engineering environment
- Experience with dimensional modeling, including Data Marts, Star and Snowflake schemas, normalization, and Slowly Changing Dimensions (SCD Type 2)
- Experience supporting Data Science and machine learning environments, including scalable model training and deployment
- Experience integrating and managing data from a variety of internal and third-party sources
- Experience working within a large, complex enterprise Data & Analytics environment
- Experience within retail, consumer, e-commerce, or another high-volume data environment
Benefits
- REMOTE
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