GCP Data Architect - 6+ years

Fractal Analytics; Bengaluru, Delhi, Mumbai; Hybrid; INR 4,500,000 - 7,500,000; Full time

Job summary

Fractal Analytics seeks an experienced Data Engineer Lead to design and deliver scalable data solutions on Google Cloud Platform. You will lead cross-functional teams to migrate data and build end-to-end pipelines using BigQuery, Airflow, DBT and Medallion Architecture.

The role requires 8–12 years of experience, strong SQL/Python skills, and a strategic mindset to optimize data platforms for analytics and decision-making.

Qualifications

• 8–12 years of experience in data engineering or a related field.
• Proven ability to design scalable data platforms on GCP with BigQuery and data pipelines.
• Experience leading cross-functional teams on data migration and end-to-end pipelines using Airflow, DBT, and Medallion Architecture.
• Strong SQL and Python (incl. PySpark) skills with hands-on cloud services.
• Ability to translate business requirements into robust data platforms and drive performance and cost optimization.

Responsibilities

• Oversee architecture and management of GCP resources (BigQuery, Databricks, Kubernetes).
• Design scalable data architectures tailored to business needs and optimize workloads for performance and cost.
• Implement monitoring and performance metrics for data pipelines and apps; manage budgets and cost control.
• Collaborate with data engineers, developers, and stakeholders to ensure seamless integration and functionality.
• Drive modernization initiatives and implement modern data architecture patterns to improve data quality and efficiency.

Skills

SQL

Python

PySpark

GCP

BigQuery

Airflow

DBT

Medallion Architecture

Kubernetes

Databricks

AlloyDB

Data Modeling

ETL

Tools

Databricks

Kubernetes

BigQuery

Job description

Job Description

• Data Engineer Lead with 8-12 years of experience in designing, building, and delivering scalable data solutions on Google Cloud Platform (GCP).
• Proven expertise in leading cross-functional teams to execute complex data migration programs and develop end-to-end data pipelines using BigQuery, Apache Airflow, DBT, and Medallion Architecture
• Strong ability to translate business requirements into robust, scalable, and efficient data platforms that support analytics and enterprise decision-making.
• Demonstrated success in driving automation and modernization initiatives. Experienced in implementing modern data architecture patterns to improve data quality, processing efficiency, and operational performance.
• Possesses strong technical expertise in SQL, Python, PySpark, and GCP services, combined with leadership capabilities, proactive problem-solving, and a passion for building high-impact data engineering solutions.

Responsibilities

• Platform Management: Oversee the architecture and management of GCP resources, particularly BigQuery, Databricks, and Kubernetes.
• Architecting Solutions: Design scalable and efficient data architectures tailored to specific business needs. Optimization of Workloads: Analyze and optimize data processing workloads to improve performance and reduce costs.
• Performance Measurement: Implement monitoring and performance metrics for data pipelines and applications. Cost Monitoring: Develop strategies for cost-effective resource usage, including budget tracking and optimization techniques.
• Collaboration: Work closely with data engineers, developers, and stakeholders to ensure seamless integration and functionality. Required Skills: GCP Expertise: In-depth knowledge of Google Cloud Platform services, particularly BigQuery, AlloyDB, and Kubernetes. Data Engineering: Experience with data modeling, ETL processes (Data flow, Data proc, Cloud functions, Cloud Run), and data warehousing (Big Query, GCS) and data ingestion (pub sub)
• Performance Tuning: Proven track record in optimizing data processing and query performance in BigQuery. Kubernetes Management: Proficient in deploying and managing containerized applications using Kubernetes.
• Cost Management: Familiarity with GCP billing and cost management tools to monitor and optimize cloud expenditure. Monitoring Tools: Experience with GCP monitoring and logging tools (e.g., Stackdriver, Cloud Monitoring).
• Required Years of Experience: 8-12 years experience