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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Everforth Apex - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Query Performance, Microsoft Access, Airflow, Big Data, BigQuery, Continuous Integration, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Visualization, Data Warehousing, Data Flow Control, Python (Programming Language), Logical Data Models, Power BI, SQL Databases, Google Cloud, Sql Optimization, Delivery Pipeline, Information Technology, Google Bigquery, Software Version Control, Data Pipelines - **Published:** September 29, 2026 - **Apply:** https://www.dice.com/job-detail/3b96972f-f6fd-4c66-9776-a77193167fe2 ## About the Role We are seeking a highly experienced Data Engineer with deep expertise in Power BI semantic model design and Google Cloud Platform BigQuery to lead data visualization initiatives within our growing analytics team. The ideal candidate brings 10+ years of experience in data engineering and business intelligence, along with a proven track record of architecting, developing, and optimizing enterprise-scale Power BI semantic models, reports, and dashboards. Strong data engineering knowledge is also essential. This role will establish best practices for querying and transforming massive datasets in BigQuery and partner with business and cross-functional stakeholders to translate reporting needs into high-performance, high-impact insights., * Bachelor's degree in Computer Science, Information Technology, or a related field. * 10+ years of Business Intelligence experience, with a strong focus on Power BI and enterprise reporting. * Advanced SQL skills and hands-on experience developing complex, optimized queries in Google BigQuery. * Strong understanding of data engineering and data warehousing, including ETL/ELT, dimensional modelling, and data pipelines. * Expert semantic model design capabilities, including advanced DAX, M-Query, star and snowflake schemas, and composite models. * Expert proficiency with Power BI Desktop and Power BI Report Builder (paginated reports). * Extensive Power BI Service experience, including publishing, security, administration, and gateway configuration. * Strong understanding of BigQuery architecture, including tables, views, materialized views, partitioning, and clustering. * Proven ability to connect Power BI to BigQuery and other sources and optimize data refresh. * Demonstrated experience gathering requirements directly from business users and documenting logic and specifications. * Excellent analytical, problem-solving, and communication skills. * Ability to work independently and collaboratively in a fast-paced agile environment. ## Description A. Business Engagement and Requirement Discovery * Meet regularly with business stakeholders, process owners, and end users to understand reporting needs, pain points, and the decisions reports must support. * Lead requirements workshops and walkthroughs of existing reports to identify gaps, manual work, and duplicate reports that can be consolidated. * Define and document KPIs, metrics, and business rules in a shared glossary, including calculation methods, filters, and sources of truth. * Document reporting logic in detail, including: + Report grain, such as dealer, contract type, or quarter + Filters, exclusions, and default values + Hierarchies, drill paths, and time-intelligence requirements + Treatment of nulls, negative values, and cancelled or reversed records * Confirm data sources, refresh frequency, and latency expectations, including daily, hourly, and near-real-time requirements. * Gather security requirements, including data visibility and row-level or object-level security. * Establish acceptance criteria, sample outputs, and sign-off requirements before development begins. * Translate business requirements into functional and technical specifications, mapping documents, and logical data models. * Prioritize the backlog with business stakeholders and establish delivery milestones using agile practices. * Lead UAT and reconciliation sessions by comparing report totals with source systems or legacy reports. * Provide user training, documentation, and ongoing support. B. Semantic Model and Data Modelling * Design and maintain enterprise Power BI semantic models using star and snowflake schemas. * Select the appropriate storage mode-Import, DirectQuery, Dual, Direct Lake, or composite models-based on data volume, freshness, and cost. * Develop robust models with: + Optimized relationships + Reusable, well-documented DAX measures and calculation groups + M-Query transformations + Role-playing dimensions + Incremental refresh and aggregation tables * Promote reusability through shared certified datasets, thin reports, and consistent business definitions across departments. * Establish standards for naming conventions, folder and measure organization, and model documentation. C. Google Cloud Platform BigQuery and Data Engineering * Write complex, optimized BigQuery SQL using CTEs, window functions, and joins across large datasets. * Apply BigQuery best practices, including partitioning, clustering, views, materialized views, query pruning, avoiding SELECT *, slot and on-demand usage management, and query performance tuning. * Collaborate with data engineers to design ETL/ELT pipelines, curated (gold) layers, and dimensional models in BigQuery. * Build reporting-ready views or tables in BigQuery so that intensive transformations occur upstream rather than in Power BI. * Ensure data accuracy, integrity, and consistency through validation checks, reconciliation, and data-quality rules. * Understand orchestration and pipeline concepts; familiarity with Dataflow, Cloud Composer/Airflow, and Python is a plus. D. Performance, Administration, and Governance * Tune report and model performance using Performance Analyzer, DAX Studio, Tabular Editor, and VertiPaq Analyzer. * Improve refresh processes through incremental refresh, query folding, and efficient partitioning. * Administer Power BI Service, including workspaces, deployment pipelines, datasets, gateways, refresh schedules, and capacity. * Implement row-level and object-level security while following data governance, access, and compliance standards. * Establish CI/CD and version control for BI assets wherever possible. * Monitor usage, refresh failures, and capacity, and proactively resolve issues. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Fully Orchestrating Databricks from Airflow](https://www.wearedevelopers.com/videos/336-fully-orchestrating-databricks-from-airflow) - [Making Data Warehouses fast. 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