Power BI Developer

Role and Responsibilities:

• Lead discovery of current reporting, BI, and data landscapes: inventory source systems, existing datasets, semantic models, KPIs, metric definitions, data gaps, and upstream/downstream dependencies.
• Design logical and physical data models for analytics use cases, including dimensional models, fact and dimension structures, conformed dimensions, aggregations, and curated reporting marts.
• Develop analytics-ready datasets using SQL and Redshift, including data transformation, joins, business rules, performance tuning, incremental loads, and data reconciliation.
• Build and maintain governed semantic layers and Power BI-ready data structures that enable self-service reporting, standardized metrics, and consistent business interpretation.
• Define and document metric logic, source-to-target mappings, lineage, grain, refresh frequency, business rules, and validation criteria for all analytical data assets.
• Implement data quality and validation checks including completeness, accuracy, duplication, referential integrity, reconciliation, and exception reporting to ensure trusted analytics outputs.
• Support Power BI dashboard development by shaping datasets, optimizing query performance, validating measures, and ensuring alignment between data models and business reporting needs.
• Collaborate with data engineering, BI, product, and business teams to deliver reusable, scalable, and well-governed analytics data products in an Agile delivery model.
• Prepare and maintain clear documentation including data dictionaries, model design notes, source-to-target mapping documents, acceptance criteria, data quality test results, and operational runbooks.
• Support migration, rationalization, and modernization of legacy reporting assets by identifying redundant datasets, retiring unused tables, and aligning future-state models to analytics requirements.
• Use SAS Viya or similar analytics platforms, where applicable, to understand legacy logic, validate analytical outputs, or support transition of existing analytical processes.

Candidate Profile:

• Bachelor's/master's degree in computer science, engineering, information systems, data analytics, operations research, or a related field.
• Strong hands-on experience in data modeling for analytics, including dimensional modeling, star/snowflake schemas, fact and dimension design, metric standardization, and reporting marts.
• Advanced SQL skills with ability to write, debug, optimize, and performance-tune complex analytical queries.
• Hands-on experience working with Redshift or similar cloud data warehouse platforms for analytics workloads.
• Experience preparing Power BI-ready datasets, semantic layers, measures, and reporting data structures to support scalable dashboards and self-service analytics.
• Ability to translate business reporting requirements into source-to-target mappings, curated datasets, reusable data assets, and well-documented analytical models.
• Strong understanding of ETL/ELT concepts, incremental loads, data transformations, reconciliation, and data quality checks for analytics engineering use cases.
• Experience documenting data dictionaries, metric definitions, lineage, grain, business rules, validation logic, and model design decisions.
• Exposure to SAS Viya or SAS-based analytical environments is preferred but not mandatory.
• Good understanding of data warehousing, BI delivery lifecycle, Agile delivery practices, and collaboration with data engineering and business teams.
• Strong analytical thinking, attention to detail, problem-solving ability, and comfort working in fast-paced, evolving client environments.
• Excellent written and verbal communication skills with ability to explain data models, assumptions, and trade-offs to technical and business stakeholders.