Senior Data Consultant - Google Cloud (Big Query, Dataproc, Data flow)

We are looking for a hands-on senior consultant who can operate across architecture, delivery, and stakeholder change management conversations- someone equally credible whiteboarding a target-state design with customer engineers and walking a business domain team through what changes for them and why.

About the Role

You will be embedded in the delivery team as a senior individual contributor with architectural authority.

Responsibilities

• ~40% Architecture- target-state and migration design, ADRs, Design Authority participation
• ~40% Delivery- hands-on build, migration factory execution, cutover validation
• ~20% Change Management & Adoption- working sessions with customer’s business and engineering teams to land the new operating model

Key Responsibilities

Architecture

• Design and evolve components of the governed lakehouse foundation: BigQuery compute, Apache Iceberg storage, batch/streaming/CDC ingestion, dbt-based transformation with CI/CD, catalog, lineage, data quality, and semantic layer.
• Produce Architecture Decision Records (ADRs) and defend designs at the Design Authority / ARB, including security, cost, and data-risk hard-stop controls.
• Assess in-scope Snowflake and Databricks workloads; define migration path (rehost / re-platform / re-architect) and migration patterns consistent with the "migrate logic, not debt" principle.
• Contribute to the AI/agentic control-plane architecture (LLM gateway, tool/MCP registry, evaluation, human-in-the-loop) where it touches the data platform.
• Ensure designs meet non-negotiables: zero downtime, trustworthy data, no partial cutover, security findings as hard stops, and cost as a first-class deliverable (dual-run spend capped at 120% of baseline).

Hands on Delivery

• Execute within the migration factory: build data pipelines and data products, implement parallel-run validation (data, performance, cost, quality) and drive workloads through cutover gates to legacy decommissioning.
• Implement federated governance mechanics in code - data contracts, DQ rules, lineage, access controls, certification workflows - where data is produced, not bolted on afterward.
• Support wave planning: workload inventory, dependency mapping, effort estimation, and sequencing by business value and risk.
• Troubleshoot production-impacting issues during dual-run and hypercare periods; contribute to operational runbooks and build-operate-transfer handover to customer teams.
• Track and report delivery evidence against wave gates (delivery, trust, adoption, economics) for steering.

Change Management & Stakeholder Engagement

• Partner with the Change Management & Enablement/Training workstream to translate platform changes into what actually changes for customer’s business domain teams: new tools, new ownership (data-as-a-product, domain stewardship), new ways of working under the hub-and-spoke model.
• Lead and facilitate working sessions with customer business and engineering stakeholders - requirements walkthroughs, disposition reviews, adoption clinics, and objection handling with teams attached to existing Snowflake/Databricks workflows.
• Coach customer engineers (data engineering, analytics engineering, platform) through pairing and enablement sessions, supporting the people-move-with-workloads principle and measurable capability transfer.
• Surface adoption risks and resistance early to the Program Leadership team with recommended mitigations.

Qualifications

• 10+ years in data engineering / data architecture, with 3+ years in client-facing consulting or professional services delivery.
• Deep, hands-on Google Cloud data stack expertise: BigQuery (modeling, performance, cost optimization), Dataproc, Dataflow or equivalent streaming/CDC, dbt, orchestration (Composer/Airflow), and CI/CD for data.
• Proven experience delivering at least one large-scale platform migration (Snowflake, Databricks, or on-prem → cloud lakehouse), including parallel-run validation and production cutover.
• Working knowledge of open table formats (Apache Iceberg preferred) and lakehouse architecture patterns.
• Practical experience implementing data governance: catalogs, lineage, data quality frameworks, data contracts, access management, and data-mesh / hub-and-spoke or federated operating models.
• Demonstrated ability to run stakeholder-facing sessions: workshops, design reviews, and difficult conversations with business teams during transformation (exposure to a structured change framework such as ADKAR is a plus).
• Strong communication in English; comfortable presenting to director/VP-level client audiences.

Preferred Skills

• Telecommunications domain experience (network data, CDR/usage data, customer 360, CLM/campaign data).
• Experience with Snowflake and/or Databricks internals sufficient to assess and translate existing workloads (Spark, Delta, Snowflake SQL/tasks/streams).
• Exposure to GenAI/agentic patterns on the data platform: semantic layers for LLM consumption, Gemini/Vertex AI, MCP/tool integration, RAG over governed data.
• FinOps literacy: cost baselining, a location/tagging, forecasting, and cost-per-workload reporting.
• MLOps/DataOps practices (feature pipelines, model CI/CD).
• Google Cloud Professional Data Engineer and/or Professional Cloud Architect certification.
• Experience working in the Philippines market or with Southeast Asian enterprise clients.