Senior Power BI Architect

We are hiring a hands-on Power BI Architect to migrate our analytics data foundation to Google Cloud Platform (GCP), with Power BI as the reporting platform and using LookML for governed business semantics. You will personally design, build, debug, and optimize complex integrations, models, and production reports. Deep Power BI tool expertise is the primary requirement, supported by practical BigQuery and LookML engineering. This is not a dashboard-only or advisory-only role.

Responsibilities:

• Engineer Power BI solutions. Build advanced DAX using filter/row context, context transition, calculation groups, and time intelligence; develop Power Query M with query folding. Design star schemas, relationships, reusable semantic models, and thin reports. Select Import, DirectQuery, composite models, aggregations, and incremental refresh only where the connection, capacity, and licensing support them.
• Lead the GCP migration. Assess existing reports, models, M queries, DAX, refresh schedules, security, and source dependencies. Define migration waves, source-to-target mappings, and remediation plans. Rebind or refactor integrations, reconcile business calculations, run parallel validation and user acceptance testing, and own cutover, rollback, and stabilization.
• Build and validate integrations. Implement BigQuery SQL and Power Query integration with enterprise databases, APIs, and files. Evaluate BigQuery and BigQuery (Microsoft Entra ID) connectors, including ADBC Implementation 2.0 versus legacy ODBC, alongside the Looker connector. Track releases, preview status, and compatibility; prove upgrades before rollout. Partner with data engineering on ingestion, CDC, and orchestration.
• Govern LookML semantics. Develop LookML models, views, explores, dimensions, measures, and joins. Define grain, primary keys, relationships, and symmetric aggregates; use persistent derived tables, datagroups, and aggregate awareness appropriately. Establish ownership of business logic across BigQuery, LookML, and DAX, with automated metric reconciliation and version-controlled changes.
• Deliver performance at scale. Diagnose DAX, VertiPaq, query plans, folding, and visual bottlenecks using Performance Analyzer, DAX Studio, and Tabular Editor. Optimize cardinality, generated SQL, BigQuery partition pruning, and pre-aggregation. Benchmark realistic concurrency, p95 report latency, refresh duration, memory, capacity, and query cost; validate cache behavior and cross-cloud transfer overhead.
• Own security, delivery, and operations. Design workspaces, apps, row-/object-level security, and least-privilege access across Power BI, Looker, and GCP. Validate identity and credential handling by connection path. Establish Git, automated tests, deployment pipelines, monitoring, and recovery runbooks; evaluate PBIP/TMDL and API automation within supported releases. Lead code reviews, mentor developers, and own production handover.

Target Integration:

• Governed path: Power BI > Looker connector (DirectQuery) > LookML-modeled Looker Explores > BigQuery. Validate the end-to-end path against the deployed versions.
• Exception path: Power BI > BigQuery (Import or DirectQuery) requires approved metrics and security parity. Direct BigQuery access does not execute LookML; do not assume all Power BI modes work through the Looker connector.

Integration Edge Cases You Must Solve:

• Metric correctness. Resolve join fan-out, duplicate keys, non-additive measures, distinct-count and matrix-total mismatches, null handling, time zones, and numeric precision changes. Reconcile source, Looker, and Power BI results.
• Connector behavior. Diagnose folding breaks, unsupported DAX/M operations, parameter/filter gaps, row limits, DATETIME and nested-field conversions, refresh failures, API quotas, and driver regressions. Validate custom-connector approval, desktop/gateway compatibility, and a tested fallback.
• Identity and networking. Validate private Looker connectivity and cross-project IAM/billing and credentials. The Looker custom connector does not provide per-viewer SSO in Power BI Service; enforce and test viewer restrictions in Power BI. Evaluate Entra ID SSO separately for direct BigQuery.
• Operational resilience. Handle CDC deletes, schema drift, late changes outside refresh windows, backfills, and idempotent retries. Resolve concurrency spikes, stale caches, region latency, throttling, and gateway failures; prove recovery without silent data loss.

Requirements:

• Experience: Typically 10+ years in BI/data engineering, including 5+ years hands-on Power BI and 3+ years in architecture or technical leadership; equivalent delivery experience is considered.
• Production ownership in Power BI Desktop and Service, including refresh/gateway operations and workspace governance, plus at least one cloud migration or major source-platform change. Demonstrable BigQuery and LookML engineering is essential; dashboard-only exposure is insufficient.
• Advanced SQL, DAX, and Power Query M; practical Python/automation, Git, CI/CD, and systematic troubleshooting. Explain your own implementation decisions with data volumes, concurrency, refresh timings, and before/after performance evidence. Relevant degree or equivalent professional experience.
• Preferred Experience: Dataflow, Datastream, Pub/Sub, Cloud Storage, Composer/Airflow and Dataform/dbt; integrations with SQL Server, Oracle/SAP, Snowflake/Databricks or REST APIs; XMLA/REST automation, paginated reports and capacity planning. Certifications are beneficial, not a substitute for delivery.