Senior GCP Data Engineer

Dentsu Global Services Private Limited; Thane; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Dentsu Global Services Private Limited in Mumbai/Thane is seeking a hands-on GCP Data Engineer to design and operate scalable data pipelines and analytics-ready data platforms on Google Cloud. You will work with analytics, AI/ML teams and architects to deliver enterprise-grade data solutions in a fast-paced environment.

The role emphasizes building reliable ETL/ELT workflows, data products, and governance, while leveraging Vertex AI, BigQuery ML, and GenAI-enabled data ecosystems.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field.
• 3–6 years of experience in data engineering and cloud-based data platform development.
• Hands-on experience with Google Cloud Platform (GCP) data services.
• Strong SQL and Python programming skills.
• Experience developing scalable ETL/ELT pipelines and distributed data processing.
• Familiarity with data lakes, data warehouses, and streaming pipelines.
• GCP certifications are a plus.

Responsibilities

• Develop and maintain scalable batch and real-time data pipelines on GCP.
• Build ingestion, transformation, and serving pipelines for analytics and AI use cases.
• Modernize legacy data workflows into cloud-native architectures.
• Develop reusable data engineering components following standards.
• Support event-driven and streaming-based data processing solutions.
• Contribute to data products and standardized data models for analytics.
• Collaborate on governance, monitoring, and operational support.

Skills

GCP Data Engineering

BigQuery

Dataflow

Dataproc

Pub/Sub

SQL

Python

PySpark

Education

Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field

Tools

Cloud Composer

Airflow

Looker

DBT

BigQuery

Job description

Job Description: Title: GCP Data engineer

About the Role We are seeking a highly motivated and hands-on GCP Data Engineer to support the development and delivery of modern enterprise data and AI platforms on Google Cloud Platform (GCP). This role will work closely with Lead Data Engineers, Enterprise Architects, analytics teams, and AI/ML teams to build scalable, reliable, and AI-ready data pipelines and cloud-native data solutions that support enterprise analytics, intelligent automation, and digital transformation initiatives. The ideal candidate should possess strong foundations in cloud data engineering, distributed data processing, and modern data platform development, along with a passion for building high-quality, scalable, and reusable data solutions in a fast-paced enterprise environment. This role offers an excellent opportunity to work on large-scale data modernization, semantic data enablement, and next-generation AI data ecosystems.

Key Responsibilities

• 1. Cloud Data Engineering & Pipeline Development Develop and maintain scalable batch and real-time data pipelines on GCP. Build ingestion, transformation, and serving pipelines supporting enterprise analytics and AI use cases. Assist in modernization of legacy data workflows into cloud-native architectures. Develop reusable and maintainable data engineering components following established architectural standards. Support implementation of event-driven and streaming-based data processing solutions.
• 2. Data Product Development Contribute to development of reusable and domain-oriented data products. Implement data transformation logic and standardized data models supporting downstream analytics and AI consumption. Support implementation of: Data quality validations
  Schema management
  Metadata enrichment
  Data contracts
  Reusable transformation frameworks Ensure data pipelines are reliable, scalable, and production-ready.
• 3. GCP Platform Development Work with GCP-native services including: BigQuery Dataflow Dataproc DBT Pub/Sub Cloud Storage Cloud Composer (Airflow) Cloud SQL Develop ETL/ELT pipelines and optimize data processing workloads. Support orchestration and scheduling of enterprise data workflows. Monitor and troubleshoot pipeline performance, failures, and operational issues.
• 4. Semantic & Analytics Enablement Support implementation of semantic models and business-friendly data structures for analytics and reporting. Collaborate with analytics and BI teams to improve consistency and usability of enterprise data assets. Assist in development of standardized metrics, dimensions, and reusable reporting datasets. Contribute to metadata and data catalog integration initiatives.
• 5. AI/ML Data Enablement Build and optimize AI-ready data pipelines supporting ML and GenAI initiatives. Support feature engineering and data preparation workflows for AI/ML use cases. Assist in integration with: Vertex AI BigQuery ML Vector databases GenAI frameworks Contribute to implementation of semantic search and AI-assisted data interaction patterns.
• 6. Engineering Best Practices & Collaboration Follow established coding standards, architecture guidelines, and DevOps practices. Participate in code reviews, testing, debugging, and performance optimization activities. Collaborate effectively with architects, lead engineers, analysts, and client stakeholders. Contribute to engineering documentation, operational runbooks, and technical knowledge sharing. Continuously learn and adopt modern cloud, data engineering, and AI platform technologies.
• 7. Governance, Monitoring & Operational Support Support implementation of monitoring, logging, lineage, and observability frameworks. Ensure adherence to enterprise security, governance, and compliance standards. Assist in incident resolution, root cause analysis, and platform stability improvements. Contribute to continuous improvement initiatives for operational excellence and delivery quality.

Technical Expertise Required

Area Skills / Technologies
Cloud Data Engineering GCP, BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage
Data Processing SQL, Python, PySpark, DBT Streaming & Pipelines Apache Beam, batch & real-time processing
Workflow Orchestration Cloud Composer (Airflow), Workflows
Semantic & Analytics Basic semantic modeling concepts, reporting datasets, Looker exposure preferred
AI/ML Enablement Vertex AI exposure, BigQuery ML, GenAI ecosystem awareness
Metadata & Governance Data Catalog, metadata management, lineage concepts
DevOps & Automation CI/CD concepts, Git, automation frameworks

Qualifications

Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field. 3–6 years of experience in data engineering and cloud-based data platform development. Hands-on experience working with Google Cloud Platform (GCP) data services. Strong SQL and Python programming skills. Experience developing scalable ETL/ELT pipelines and distributed data processing workflows. Understanding of modern data architecture concepts including data lakes, data warehouses, and streaming pipelines. Exposure to analytics, AI/ML, or GenAI-enabled data ecosystems preferred. Strong analytical, troubleshooting, and problem-solving skills. Ability to work collaboratively in Agile and cross-functional delivery teams. GCP certifications such as Associate Cloud Engineer or Professional Data Engineer are a plus.

Preferred Experience

Exposure to enterprise-scale data modernization initiatives. Familiarity with modern data engineering and data product development practices. Experience working with semantic layers, reporting platforms, or BI ecosystems. Exposure to AI-ready data platforms and modern analytics ecosystems. Experience in retail, marketing, customer analytics, or digital commerce domains is an advantage.

Location: DGS India - Mumbai - Thane Ashar IT Park Brand: Merkle Time Type: Full time Contract Type: Permanent

About dentsu

About dentsu For over 120 years, innovation has been a core tenet of our offering – exploring new ways to reach, engage and nurture relationships with audiences. Together we drive a multiplier effect for clients at a global scale, through the development of Integrated Growth Solutions that are underpinned by our promise to clients: innovating to impact. Be a force for good. Sustainability is a vital part of our business and an important area of focus for our clients. We’re leading the way – helping to build a more sustainable planet. Dream loud. In this moment of transformation, we need our people to be fearless, embracing change and ambiguity, driven by the love for our work and excitement for the future. Team without limits. We create opportunities for connection and collaboration between our colleagues and clients, building a sense of belonging and having some fun along the way. Find out more about us Who we are Our Social Impact Our work