Data Engineering Architect

1 day ago

Pune, Maharashtra, India Bean Hr Consulting Full time ₹ 1,20,000 - ₹ 4,20,000 per year

Job Title: Google Data Engineering Architect

Location: Pune, India

Experience: 68 years

Maximum Budget: 35 LPA

About the Role

We are looking for a highly skilled Data Engineering Architect to join our team in Pune. In this role, you will design, build, and scale Google's large-scale data infrastructure. You will be a technical leader, driving innovation, ensuring data quality, and mentoring a team of engineers. This is a high-impact role ideal for someone passionate about big data, cloud technologies, and architecting complex data systems.

Key Responsibilities

Design & Architecture:

  • Design and implement scalable, reliable, and efficient data architectures for Google products and services.
  • Develop and maintain data models, schemas, and ontologies to support diverse data sources.
  • Evaluate and recommend emerging data technologies to enhance the data infrastructure.
  • Collaborate with product managers, engineers, and researchers to define data requirements and translate them into technical solutions.

Data Processing & Pipelines:

  • Build and optimize batch and real-time data pipelines using GCP services such as Dataflow, Dataproc, Pub/Sub, and Cloud Functions.
  • Implement data quality checks and validation processes to ensure data accuracy and consistency.
  • Define and enforce data governance policies for security and compliance.

Data Storage & Management:

  • Architect scalable data storage solutions using BigQuery, Cloud Storage, and Spanner.
  • Optimize data storage and retrieval for performance and cost-effectiveness.
  • Implement data lifecycle management policies including retention, archiving, and deletion.

Team Leadership & Mentorship:

  • Provide technical guidance to data engineers and team members.
  • Mentor junior engineers to build expertise in data engineering best practices.
  • Foster a culture of innovation, collaboration, and continuous learning within the team.

Required Qualifications

  • 6–8 years of experience in data engineering or related fields.
  • Strong understanding of data warehousing, data modeling, and ETL/ELT processes.
  • Proven expertise in designing and implementing large-scale data pipelines and architectures.
  • Proficiency in SQL and at least one programming language (Python or Java).
  • Hands-on experience with GCP services: BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Spanner.
  • Experience with big data frameworks: Hadoop, Spark, Kafka.
  • Excellent communication, collaboration, and problem-solving skills.

Preferred Qualifications

  • Experience in data governance and quality management.
  • Familiarity with machine learning and data science workflows.
  • Knowledge of Docker, Kubernetes, and cloud-based orchestration.
  • Contributions to open-source projects or communities.
  • Google Cloud Professional Data Engineer certification.

Technical Skills Summary

Mandatory:

  • GCP (BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage)
  • SQL & Python/Java
  • Data modeling, ETL/ELT, data warehousing
  • Batch & real-time data pipelines
  • Big data frameworks: Hadoop, Spark, Kafka

Preferred:

  • Data governance and quality management
  • Machine learning & data science pipelines
  • Docker & Kubernetes

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