Power BI Architect (GCP)

Experience: 10+ Years

Location: Manyata, Bangalore

Mode of work: 3-4 Days at office

GCP Migration & LookML Semantic Modeling

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 considered.

THE ROLE

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.

KEY 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-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.

INTEGRATION
- Governed path: Power BI > Looker connector (Direct Query) > 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 metric 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. [1,2,5]
- 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. [1,2]
- Identity and networking. Validate private Looker connectivity, 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. [1,3]
- 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.

REQUIRED EXPERIENCE

- 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 skilled 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.

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