Data Architect

Tredence; Pune District, Gurugram District, Bengaluru; Hybrid; INR 4,200,000 - 6,400,000; Full time

Job summary

Tredence seeks a senior Data Architect to design and govern enterprise-grade data architectures on GCP. You will lead data platform strategies, build scalable data lakes and lake house solutions, and guide migrations from on-premises to GCP while collaborating with stakeholders across teams.

Responsibilities include defining standards, data governance, metadata and MDM, and ensuring security compliance. Strong expertise in SQL and Python/Java/Scala is required, with 12-18 years of IT experience

Qualifications

• 12-18 years of IT experience with significant experience in Data Architecture.
• Strong hands-on expertise in BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Cloud Storage and related GCP services.
• Experience with data modeling, ETL/ELT, data warehousing, and lake house architectures.
• Proficiency in SQL and Python/Java/Scala.
• Knowledge of data governance, data quality, and cloud security frameworks.

Responsibilities

• Design and implement enterprise-grade data architectures leveraging GCP services.
• Define and govern end-to-end data strategy, architecture standards, and best practices.
• Architect scalable data lakes, data warehouses, lake house solutions, and real-time data platforms.
• Lead cloud data transformation and migration initiatives from on-premises and multi-cloud environments to GCP.
• Design batch and streaming data pipelines using GCP-native technologies.
• Collaborate with business stakeholders, data engineers, analysts, and application teams to understand requirements and translate them into scalable solutions.
• Establish data governance, metadata management, master data management (MDM), and data quality frameworks.
• Ensure compliance with security, privacy, and regulatory requirements.
• Optimize platform performance, scalability, reliability, and cost efficiency.
• Mentor technical teams and provide architectural guidance across multiple projects.
• Conduct architecture reviews and recommend improvements aligned with business objectives.

Skills

BigQuery

Dataflow

Dataproc

Pub/Sub

Cloud Composer

Cloud Storage

SQL

Python

Java

Scala

Data Modeling

ETL/ELT

Data Warehousing

Lake House Architecture

GCP

Data Governance

Data Quality

Cloud Security

Tools

Spark

Kafka

Airflow

Terraform

AI/ML Data Platforms

Job description

Key Responsibilities

• Design and implement enterprise-grade data architectures leveraging GCP services.
• Define and govern end-to-end data strategy, architecture standards, and best practices.
• Architect scalable data lakes, data warehouses, lake house solutions, and real-time data platforms.
• Lead cloud data transformation and migration initiatives from on-premises and multi-cloud environments to GCP.
• Design batch and streaming data pipelines using GCP-native technologies.
• Collaborate with business stakeholders, data engineers, analysts, and application teams to understand requirements and translate them into scalable solutions.
• Establish data governance, metadata management, master data management (MDM), and data quality frameworks.
• Ensure compliance with security, privacy, and regulatory requirements.
• Optimize platform performance, scalability, reliability, and cost efficiency.
• Mentor technical teams and provide architectural guidance across multiple projects.
• Conduct architecture reviews and recommend improvements aligned with business objectives.

Required Skills:

• 12-18 years of IT experience with significant experience in Data Architecture.
• Strong hands-on expertise in BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, Cloud Storage, and related GCP services.
• Experience with data modeling, ETL/ELT, data warehousing, and lake house architectures.
• Proficiency in SQL and Python/Java/Scala.
• Knowledge of data governance, data quality, and cloud security frameworks.

Preferred:

• GCP Professional Data Engineer certification.
• Experience with Spark, Kafka, Airflow, Terraform, and AI/ML data platforms.