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

HCL Technologies Philippines Inc; Pateros; On-site; PHP 1,800,000 - 3,000,000; Full time

Job summary

HCL Technologies Philippines Inc. seeks a hands-on senior consultant to operate across architecture, delivery, and stakeholder change management conversations.

Embedded in the delivery team, you will have architectural authority and oversee migration design, run dual-run validation, and drive cutover to legacy environments. The role emphasizes design authority participation, hands-on data pipelines, and governance, with a focus on cloud data platforms (BigQuery, Snowflake, Databricks) and

Qualifications

• 10+ years in data engineering or data architecture.
• 3+ years in client-facing consulting or professional services delivery.
• Hands-on Google Cloud data stack expertise with multiple platform migrations.
• Strong ability to run stakeholder-facing workshops and ADRs.

Responsibilities

• Architect design of lakehouse components and migration patterns.
• Deliver hands-on data pipelines, cutover validation, and dual-run success.
• Lead change management activities and stakeholder sessions with business teams.
• Define governance: data contracts, lineage, access controls, and certification workflows.
• Collaborate with client teams to land the new operating model.

Skills

BigQuery

Dataproc

Dataflow

dbt

Composer/Airflow

CI/CD for data

Snowflake

Databricks

Apache Iceberg

Data governance

stakeholder engagement

Tools

Snowflake

Databricks

Apache Iceberg

BigQuery

dbt

Airflow/Composer

CI/CD tooling

Job description

About the Company

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.

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. What Success Looks Like (First 90 Days) Trusted technical counterpart to at least one customer workstream lead; contributing ADRs accepted by the Design Authority.

Hands-on delivery contribution to Wave 1 disposition and pilot build, with at least one workload validated through parallel run. Running enablement/adoption sessions independently with customer engineering teams, with positive stakeholder feedback and documented capability transfer. Equal Opportunity Statement

We are committed to diversity and inclusivity.