Data Engineer (GCP)

Loreal; Hyderabad; Hybrid; INR 700.000 - 1.000.000; Vollzeit

Zusammenfassung

L'Oréal Beauty Tech Data Platform in Hyderabad is seeking a Senior Data Engineer to lead the design, implementation, and evolution of enterprise-scale data solutions on Google Cloud Platform. You will guide engineering teams, define scalable architectures, and ensure secure, high-performing data products that drive business value.

You will mentor engineers, establish engineering best practices, and ensure efficient delivery of data platform initiatives, including data governance, security, and

Qualifikationen

• 7+ years of data engineering experience
• Experience in leadership, architecture, mentoring or project leadership
• Experience delivering large-scale production-grade data platforms
• Designing and supporting scalable cloud-native data solutions
• Leading engineering teams and coordinating technical implementations
• Supporting product roadmaps and technical vision

Aufgaben

• Design and implement large-scale data architectures on GCP.
• Define standards, patterns and engineering best practices.
• Lead architectural discussions and provide technical direction.
• Ensure scalability, security, reliability, and maintainability of data solutions.
• Drive optimization of data pipelines and BigQuery workloads.
• Build and maintain scalable data pipelines for analytics and BI.
• Mentor junior and mid-level engineers and lead governance.

Kenntnisse

Python

SQL

BigQuery

GCP

Data Vault

SCD

API development

Docker

Terraform

DevOps

CI/CD

Security OWASP

Data governance

Agile

Leadership

Tools

Terraform

Docker

CI/CD tooling

Jobbeschreibung

L'Oréal Beauty Tech Data Platform is seeking a highly skilled and experienced senior data engineer to drive the design, implementation, and evolution of enterprise-scale data solutions on Google Cloud Platform (GCP). This role combines deep technical expertise with leadership capabilities to guide engineering teams, define scalable architectures, ensure platform sustainability, and deliver secure, high-performing data products that enable business value. The Lead Data Engineer will be responsible for mentoring engineers, establishing engineering best practices, driving technical excellence, and ensuring efficient execution of data platform initiatives.

The core responsibilities for the job include the following:

Technical Leadership:

• Design and implement large-scale, end-to-end data architectures on Google Cloud Platform (GCP).
• Define technical standards, architecture patterns, and engineering best practices.
• Lead architectural discussions and provide technical direction for complex data initiatives.
• Ensure scalability, security, reliability, and maintainability of enterprise data solutions.
• Drive optimization initiatives for data pipelines, BigQuery workloads, and cloud resources.

Data Engineering and Platform Development:

• Build and maintain scalable data pipelines supporting analytics and business intelligence use cases.
• Develop advanced data models, including Data Vault architecture, Slowly Changing Dimensions (SCD), and other complex modeling patterns.
• Create custom frameworks and advanced processing solutions using Python.
• Implement Infrastructure as Code (IaC) using Terraform.
• Develop and manage containerized and serverless solutions using Docker and cloud-native technologies.
• Design secure APIs and ensure adherence to OWASP security standards.

Team Leadership and Mentorship:

• Lead technical teams through task allocation, code reviews, and engineering governance.
• Mentor junior and mid-level engineers through coaching, pair programming, and knowledge-sharing initiatives.
• Design and execute onboarding plans and capability-building programs.
• Foster a collaborative engineering culture focused on continuous improvement and technical excellence.

Project and Stakeholder Management:

• Translate business requirements into scalable technical solutions.
• Estimate effort, manage priorities, and oversee end-to-end delivery of data projects.
• Collaborate with product owners, business analysts, BI developers, and business stakeholders.
• Support technical product vision and contribute to backlog prioritization and technical user story creation.

Governance and Operational Excellence:

• Establish and enforce data governance standards, engineering practices, and quality controls.
• Identify, assess, and mitigate technical and delivery risks proactively.
• Track and manage technical debt while promoting software craftsmanship principles.
• Support full application lifecycle management from design to production support.

Requirements:

• Minimum 7+ years of data engineering experience.
• Minimum 2+ years in technical leadership, architecture, mentoring, or project leadership roles.
• Experience delivering large-scale production-grade data platforms.
• Proven experience designing and supporting scalable cloud-native data solutions.
• Demonstrated ability to lead engineering teams and coordinate technical implementations.
• Experience supporting product roadmaps and driving technical vision.

Cloud and Data Technologies:

• Strong expertise in Google Cloud Platform (GCP).
• BigQuery performance optimization and cost management.
• Data architecture and enterprise-scale solution design
• Advanced data modeling techniques (Data Vault, SCD, dimensional modeling).

Programming and Development:

• Advanced Python development for data engineering frameworks and complex processing.
• SQL and advanced query optimization.
• API development and integration.

DevOps and Infrastructure:

• Terraform (Infrastructure as Code).
• Docker and containerization.
• Serverless architecture.
• CI/CD and deployment best practices.

Security and Governance:

• Data governance frameworks.
• Security best practices and OWASP standards.
• Risk management and compliance awareness.

Agile Delivery:

• Strong understanding of Agile methodologies and ceremonies.
• Experience working in cross-functional product teams.

Leadership Competencies:

• Technical leadership and architectural decision-making.
• Team mentoring and capability development.
• Excellent communication and stakeholder management.
• Strategic thinking and problem-solving.
• Collaboration and cross-functional teamwork.
• Strong project management and execution capabilities.
• Ability to influence technical direction and product vision.

Mandatory Certifications:

• Google Cloud Certified - Professional Data Engineer.
• Google Cloud Certified - Professional Cloud Architect.

Preferred Certifications:

• ITIL Certification.
• Security Certifications.
• DevOps Certifications.
• Terraform Certification.

Nice to Have:

• Knowledge of sustainable and environmentally conscious technology practices.
• Experience in enterprise data platform modernization initiatives.
• Exposure to global and cross-functional delivery environments.