GCP - Senior Data Engineer / Data Architect
Chennai · Staff/Principal
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Job description
Job Information
Requisition Title
GCP - Senior Data Engineer/Architect
Description
As an Senior Data Engineer/Architect - GCP, you will lead enterprise-scale cloud data transformation programs, define cloud and data platform strategies, drive architecture governance, and oversee delivery of modern data, analytics and Generative AI solutions on Google Cloud Platform (GCP). You will partner with executive stakeholders, business leaders, solution architects, and engineering teams to deliver scalable, secure, and high-impact cloud solutions while building and growing high-performing teams.
• Define and drive enterprise cloud data and analytics strategy leveraging Google Cloud Platform (GCP).
• Lead architecture, design, and delivery of large-scale cloud-native data platforms, lakehouses, data warehouses, and AI-enabled data ecosystems.
• Own end-to-end cloud transformation engagements including migration, modernization, optimization, governance, and operational excellence initiatives.
• Provide executive-level technology leadership across Data Engineering, Advanced Analytics and Generative AI programs.
• Establish architecture standards, design frameworks, reference architectures, and best practices across cloud data platforms.
• Lead solution architecture reviews and ensure alignment with scalability, reliability, security, compliance, and cost optimization objectives.
• Drive adoption of modern GCP services including BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, BigLake, Vertex AI, Cloud Run, and Cloud Storage.
• Partner with business stakeholders and clients to define technology roadmaps and translate strategic objectives into scalable technical solutions.
• Lead multiple delivery teams and large transformation programs while ensuring quality, predictability, and customer success.
• Drive innovation initiatives leveraging AI/ML, Generative AI, MLOps, and intelligent automation capabilities.
• Establish governance models covering data quality, metadata management, lineage, security, privacy, and regulatory compliance.
• Lead cloud cost management, platform optimization, capacity planning, and FinOps initiatives.
• Drive adoption of DevOps, DataOps, CI/CD, Infrastructure as Code (IaC), automation, and platform engineering best practices.
• Collaborate with sales, pre-sales, and account leadership teams to support solutioning, proposals, client presentations, and business development opportunities.
• Build and mentor high-performing teams of architects, engineering managers, and senior data engineers.
• Provide thought leadership on emerging cloud technologies, modern data architectures, AI platforms, and industry best practices.
• Serve as a trusted advisor to executive stakeholders and clients on cloud, data, and AI transformation journeys.
Roles & Responsibilities
• 10+ years of experience in Data Engineering, Cloud Architecture, Data Platforms, Analytics, and Enterprise Technology Consulting.
• 7+ years of deep experience architecting and delivering enterprise-scale solutions on Google Cloud Platform (GCP).
• Proven experience leading large-scale cloud transformation and modernization programs for enterprise customers.
• Strong expertise across BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, BigLake, Cloud Storage, Vertex AI, Cloud Functions, and Cloud Run.
• Extensive experience designing and implementing modern data warehouses, data lakes, lakehouses, streaming platforms, and analytical ecosystems.
• Strong understanding of enterprise architecture principles, cloud governance, security, compliance, and risk management frameworks.
• Experience leading AI/ML and Generative AI initiatives, including data foundations, feature engineering platforms, MLOps, and model deployment architectures.
• Expertise in distributed data processing, scalable platform design, and cloud-native engineering practices.
• Strong understanding of Infrastructure as Code (Terraform), CI/CD, DevOps, DataOps, observability, and platform reliability engineering.
• Experience managing cloud economics, cost optimization strategies, and FinOps practices.
• Strong proficiency in Python, SQL, and modern data engineering frameworks.
• Proven ability to lead architecture governance, executive stakeholder management, and enterprise solution reviews.
• Demonstrated success in managing and mentoring large engineering and architecture teams.
• Strong communication, consulting, client management, and business partnering skills.
• Experience working within Agile delivery frameworks and modern product engineering methodologies.
Mandatory Skills
GCP Cloud,Gcp Architect,Pyspark
Role
Job Information
Requisition Title
GCP - Senior Data Engineer/Architect
Description
As an Senior Data Engineer/Architect - GCP, you will lead enterprise-scale cloud data transformation programs, define cloud and data platform strategies, drive architecture governance, and oversee delivery of modern data, analytics and Generative AI solutions on Google Cloud Platform (GCP). You will partner with executive stakeholders, business leaders, solution architects, and engineering teams to deliver scalable, secure, and high-impact cloud solutions while building and growing high-performing teams.
• Define and drive enterprise cloud data and analytics strategy leveraging Google Cloud Platform (GCP).
• Lead architecture, design, and delivery of large-scale cloud-native data platforms, lakehouses, data warehouses, and AI-enabled data ecosystems.
• Own end-to-end cloud transformation engagements including migration, modernization, optimization, governance, and operational excellence initiatives.
• Provide executive-level technology leadership across Data Engineering, Advanced Analytics and Generative AI programs.
• Establish architecture standards, design frameworks, reference architectures, and best practices across cloud data platforms.
• Lead solution architecture reviews and ensure alignment with scalability, reliability, security, compliance, and cost optimization objectives.
• Drive adoption of modern GCP services including BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, BigLake, Vertex AI, Cloud Run, and Cloud Storage.
• Partner with business stakeholders and clients to define technology roadmaps and translate strategic objectives into scalable technical solutions.
• Lead multiple delivery teams and large transformation programs while ensuring quality, predictability, and customer success.
• Drive innovation initiatives leveraging AI/ML, Generative AI, MLOps, and intelligent automation capabilities.
• Establish governance models covering data quality, metadata management, lineage, security, privacy, and regulatory compliance.
• Lead cloud cost management, platform optimization, capacity planning, and FinOps initiatives.
• Drive adoption of DevOps, DataOps, CI/CD, Infrastructure as Code (IaC), automation, and platform engineering best practices.
• Collaborate with sales, pre-sales, and account leadership teams to support solutioning, proposals, client presentations, and business development opportunities.
• Build and mentor high-performing teams of architects, engineering managers, and senior data engineers.
• Provide thought leadership on emerging cloud technologies, modern data architectures, AI platforms, and industry best practices.
• Serve as a trusted advisor to executive stakeholders and clients on cloud, data, and AI transformation journeys.
Roles & Responsibilities
• 10+ years of experience in Data Engineering, Cloud Architecture, Data Platforms, Analytics, and Enterprise Technology Consulting.
• 7+ years of deep experience architecting and delivering enterprise-scale solutions on Google Cloud Platform (GCP).
• Proven experience leading large-scale cloud transformation and modernization programs for enterprise customers.
• Strong expertise across BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, BigLake, Cloud Storage, Vertex AI, Cloud Functions, and Cloud Run.
• Extensive experience designing and implementing modern data warehouses, data lakes, lakehouses, streaming platforms, and analytical ecosystems.
• Strong understanding of enterprise architecture principles, cloud governance, security, compliance, and risk management frameworks.
• Experience leading AI/ML and Generative AI initiatives, including data foundations, feature engineering platforms, MLOps, and model deployment architectures.
• Expertise in distributed data processing, scalable platform design, and cloud-native engineering practices.
• Strong understanding of Infrastructure as Code (Terraform), CI/CD, DevOps, DataOps, observability, and platform reliability engineering.
• Experience managing cloud economics, cost optimization strategies, and FinOps practices.
• Strong proficiency in Python, SQL, and modern data engineering frameworks.
• Proven ability to lead architecture governance, executive stakeholder management, and enterprise solution reviews.
• Demonstrated success in managing and mentoring large engineering and architecture teams.
• Strong communication, consulting, client management, and business partnering skills.
• Experience working within Agile delivery frameworks and modern product engineering methodologies.
Experience
7 to 15 years
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