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.

Work arrangement
Hybrid