Position: Data Engineer – Power BI & Google BigQuery
Experience: 7+ years in Data Engineering; ideally 10+ years in Business Intelligence and Data Engineering
Education: Bachelor's degree in Computer Science, Information Technology, or a related field (required)
Work Arrangement: Hybrid – 4 days onsite per week
Primary Skill: Business Intelligence
Job Summary
We are seeking an experienced Data Engineer with advanced expertise in Power BI semantic modeling and Google Cloud BigQuery. The ideal candidate will have a strong background in enterprise business intelligence, data engineering, data warehousing, and performance optimization.
The candidate will design and maintain enterprise-scale Power BI semantic models, develop complex BigQuery SQL queries, optimize reporting performance, and collaborate with business and technical stakeholders to deliver accurate, scalable, and actionable analytics solutions.
Key Responsibilities
1. Power BI Development and Semantic Modeling
Design, develop, and maintain enterprise semantic models using star and snowflake schemas.
Develop reusable DAX measures, calculation groups, and Power Query (M) transformations.
Implement appropriate storage modes, including Import, DirectQuery, Dual, Direct Lake, and composite models.
Build optimized reports, dashboards, paginated reports, aggregation tables, and incremental refresh solutions.
Promote certified shared datasets, thin reports, standardized business definitions, and model documentation.
Optimize report and model performance using Performance Analyzer, DAX Studio, Tabular Editor, and VertiPaq Analyzer.
2. Google BigQuery and SQL Optimization
Develop and optimize complex SQL queries using CTEs, window functions, and large-scale joins.
Implement BigQuery partitioning, clustering, views, and materialized views.
Optimize query execution, processing costs, and performance for large datasets.
Build reporting-ready tables and views to support Power BI reporting.
Collaborate with data engineering teams to ensure efficient upstream data transformations.
3. Data Engineering and Warehousing
Develop and support ETL/ELT pipelines and curated data layers.
Design dimensional models and reporting-ready datasets.
Implement data validation, reconciliation, and data quality rules.
Improve refresh performance through query folding, incremental refresh, and efficient partitioning.
Understand pipeline orchestration and scheduling concepts. Experience with Python, Dataflow, or Cloud Composer/Airflow is preferred.
4. Power BI Administration and Governance
Manage Power BI Service workspaces, gateways, deployment pipelines, publishing, and refresh schedules.
Implement row-level security (RLS) and object-level security (OLS).
Support CI/CD, version control, access governance, and compliance requirements.
Monitor report usage, refresh failures, and capacity utilization.
Establish standards for performance, security, documentation, and enterprise reporting.
5. Business Engagement and Requirements Gathering
Partner with business stakeholders and end users to understand reporting needs and business objectives.
Lead requirements workshops and evaluate existing reports to identify gaps and opportunities for improvement.
Define and document KPIs, metrics, business rules, data sources, refresh expectations, and security requirements.
Translate business needs into functional specifications, technical requirements, data mappings, and logical data models.
Document report logic, including data grain, filters, exclusions, hierarchies, drill paths, time intelligence, and record-handling rules.
Prioritize backlogs, define milestones and acceptance criteria, and lead user acceptance testing (UAT).
Reconcile reporting results against source systems and legacy reports.
Provide user training, technical documentation, and ongoing support.
Required Qualifications
Bachelor's degree in Computer Science, Information Technology, or a related field.
7+ years of relevant Data Engineering experience, with ideally 10+ years of Business Intelligence and enterprise reporting experience.
Advanced hands-on Power BI expertise, including semantic modeling, DAX, Power Query (M), dimensional modeling, composite models, and paginated reports.
Strong SQL skills and practical experience optimizing queries in Google BigQuery.
Solid understanding of data warehousing, ETL/ELT, data pipelines, dimensional modeling, and data quality.
Experience administering Power BI Service, managing workspaces and gateways, implementing security, and optimizing refresh performance.
Experience gathering requirements, defining KPIs, documenting reporting logic, and validating results with business stakeholders.
Strong analytical, problem-solving, communication, and collaboration skills.
Ability to work independently and effectively in an Agile environment.
Preferred Qualifications
Experience with Python, Google Cloud Dataflow, Cloud Composer, or Apache Airflow.
Familiarity with DAX Studio, Tabular Editor, VertiPaq Analyzer, and Performance Analyzer.
Experience with BI CI/CD, version control, enterprise governance, and capacity management.
Strong business analysis and stakeholder management capabilities.
Key Skills
Must-Have: Power BI, DAX, Power Query (M), Google BigQuery, SQL, semantic modeling, dimensional modeling, ETL/ELT, data warehousing, and Power BI Service.
Preferred: Business Analysis, Python, Dataflow, Cloud Composer/Airflow, CI/CD, and advanced performance optimization.
Work Arrangement
This is a hybrid position requiring the selected candidate to work onsite four days per week.
