Consultant-GCP Data Engineer

Evalueserve; Gurugram District; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Evalueserve in Gurugram, India is seeking a GCP Data Engineer to design, build, deploy, and optimize scalable data pipelines on Google Cloud. The role focuses on data integration, transformation, governance, and production delivery, supported by DevOps automation.

You will work with Dataflow, BigQuery, Cloud Composer, Terraform, and Dataplex to deliver reliable data solutions for stakeholders, ensure data quality and security, and collaborate with data scientists and analysts to translate

Qualifications

• 4+ years of relevant data engineering experience on Google Cloud.
• Strong proficiency in Python and SQL for data processing and automation.
• Hands-on experience with BigQuery, Cloud Storage, Dataflow, Dataplex, and Cloud Composer.
• Experience with Apache Beam or Spark.
• Terraform for infrastructure as code.
• Experience building CI/CD pipelines with Cloud Build.
• Understanding of data warehouse, data lake, and lakehouse architectures.
• Experience integrating SQL Server, Couchbase, REST APIs, and file/object sources.
• Knowledge of data security, governance, observability, and compliance.
• Google Cloud Professional Data Engineer certification.

Responsibilities

• Design and implement scalable batch and streaming ETL/ELT pipelines using Dataflow, Apache Beam or Spark, BigQuery, and Cloud Storage.
• Integrate data from SQL Server, Couchbase, APIs, files, and event-driven sources into governed data warehouses, data lakes, or lakehouse platforms.
• Transform raw data into analytics-ready datasets using SQL, Python, dbt, and Dataflow; apply dimensional and analytical modeling practices.
• Build, schedule, monitor, and support workflows using Cloud Composer and related Google Cloud services.
• Monitor and tune pipelines, queries, storage patterns, and compute usage for reliability, throughput, scalability, and cost efficiency.
• Implement data quality rules, lineage, observability, and governance using Dataplex and related capabilities.
• Apply least-privilege access, secure data handling, encryption, auditability, retention, and privacy controls.
• Provision and manage Google Cloud resources with Terraform; create automated build, test, deployment, and release workflows using Cloud Build and source-control practices.
• Use Pub/Sub, Cloud Functions, and Datastream for near-real-time ingestion and change data capture where applicable.
• Collaborate with data scientists, analysts, application teams, security, platform engineering, and business stakeholders to translate requirements into dependable data solutions.
• Maintain architecture diagrams, data mappings, runbooks, operational procedures, deployment documentation, and coding standards.
• Track and assess relevant Google Cloud data, DevOps, and AI platform developments for enterprise data-engineering use cases.

Skills

Python

SQL

CI/CD

Education

Google Cloud Professional Data Engineer

Tools

BigQuery

Dataflow

Cloud Storage

Dataplex

Cloud Composer

Apache Beam

Spark

Terraform

Cloud Build

Job description

Job Description

Job Summary

The GCP Data Engineer will design, build, deploy, and optimize scalable data pipelines and analytics solutions on Google Cloud. The role is primarily focused on data integration, transformation, orchestration, modeling, quality, governance, performance, and reliable production delivery, supported by practical DevOps automation. The role requires 4+ years of relevant data engineering experience.

• Data pipeline engineering: Design and implement scalable batch and streaming ETL/ELT pipelines using Dataflow, Apache Beam or Spark, BigQuery, and Cloud Storage.
• Data integration: Integrate data from SQL Server, Couchbase, APIs, files, and event-driven sources into governed data warehouses, data lakes, or lakehouse platforms.
• Data transformation and modeling: Transform raw data into trusted, analytics-ready datasets using SQL, Python, dbt, and Dataflow; apply sound dimensional and analytical modeling practices.
• Orchestration: Build, schedule, monitor, and support workflows using Cloud Composer and appropriate Google Cloud services.
• Performance and cost optimization: Monitor and tune pipelines, queries, storage patterns, and compute usage for reliability, throughput, scalability, and cost efficiency.
• Data quality and governance: Implement validation rules, reconciliation controls, observability, lineage, metadata, anomaly detection, and data-quality standards using Dataplex and related capabilities.
• Security and compliance: Apply least-privilege access, secure data handling, encryption, auditability, retention, and privacy controls in alignment with organizational and regulatory requirements.
• DevOps and automation: Provision and manage Google Cloud resources with Terraform; create automated build, test, deployment, and release workflows using Cloud Build and source-control practices.
• Event-driven solutions: Use Pub/Sub, Cloud Functions, and Datastream where applicable for near-real-time ingestion, change data capture, and event-driven processing.
• Collaboration and delivery: Partner with data scientists, analysts, application teams, security, platform engineering, and business stakeholders to translate requirements into dependable data solutions.
• Documentation and standards: Maintain architecture diagrams, data mappings, runbooks, operational procedures, deployment documentation, and coding standards.
• Innovation: Track relevant Google Cloud data, DevOps, and AI platform developments and assess their practical application to enterprise data-engineering use cases.

Required Qualifications

• 4+ years of relevant experience in data engineering, including production delivery on Google Cloud.
• Strong proficiency in Python and SQL for data processing, automation, testing, and analytical querying.
• Hands-on experience with BigQuery, Cloud Storage, Dataflow, Dataplex, and Cloud Composer.
• Experience with Apache Beam or Spark and distributed data-processing patterns.
• Practical knowledge of Terraform for reusable, version-controlled infrastructure as code.
• Experience building CI/CD pipelines with Cloud Build, including automated validation, testing, packaging, and deployment.
• Understanding of data warehouse, data lake, and lakehouse principles, including distributed data architectures and data modeling.
• Experience integrating SQL Server, Couchbase, REST APIs, and file or object-storage sources.
• Knowledge of data security, privacy, governance, observability, and compliance best practices.
• Strong troubleshooting, problem-solving, documentation, stakeholder communication, and delivery skills for complex projects and tight timelines.
• Google Cloud Professional Data Engineer certification.

Disclaimer: The following job description serves as an informative reference for the tasks you may be required to perform. However, it does not constitute an integral component of your employment agreement and is subject to periodic modifications to align with evolving circumstances.

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