Data Architect

Nitor; Pune District; Hybrid; INR 3,000,000 - 6,000,000; Full time

Job summary

Nitor infotech in Pune, India seeks an experienced Data Architect to lead design and implementation of large-scale data platforms. You will shape data models, pipelines, and governance while collaborating with cross-functional teams to ensure scalable, secure data solutions.

The role requires strong expertise in Python, Spark, Kafka, SQL/NoSQL, and Google Cloud services, with emphasis on architecture, reliability, and performance.

Qualifications

• Strong experience in designing and architecting large-scale data platforms and distributed data processing systems.
• Hands-on Python development for data processing and ETL/ELT pipelines.
• Experience with Apache Spark/PySpark, Kafka, and distributed data processing.
• Expertise in data modeling, integration, ETL/ELT pipelines, and data warehousing.
• Proficient in SQL and NoSQL databases; design of scalable data solutions.
• GCP cloud services and architecture (BigQuery, GCS, Pub/Sub, Dataflow, Dataproc, Cloud Run, Workflows).
• Understanding of distributed systems, event-driven design, scalability, and fault tolerance.
• Experience with Docker, Kubernetes, CI/CD; performance tuning of data pipelines.
• Knowledge of cloud security and data governance on GCP.

Responsibilities

Skills

Data architecture

Data engineering

Distributed systems

Python

Spark/PySpark

Kafka

SQL

NoSQL

GCP Cloud Architecture

BigQuery

Dataflow

Dataproc

Cloud Run

Kubernetes

CI/CD

Docker

Observability

Tools

Docker

Kubernetes

CI/CD

GCP tools

Job description

Hi ,
Greetings from Nitor infotech!
I hope this message finds you well. My name is Vignesh, and I'm from TA Team atNitor. I am reaching out to you because I believe you may be a strong fitfora fantasticjobopportunity, we currently have
Please find below the Company Job Description with this mail.

1. Skillset: Data Architect Data Engineering, Distributed Systems, GCP Cloud Architecture
2. Experience Level: 8+ Years
3. Required Skills:
4. Strong experience in designing and architecting large-scale data platforms and distributed data processing systems.
5. Strong programming experience in Python, with hands-on experience in developing data processing and ETL/ELT pipelines.
6. Hands-on experience with Apache Spark/PySpark, Kafka, and distributed data processing.
7. Strong understanding of data architecture, data modeling, data integration, ETL/ELT pipelines, and data warehousing.
8. Strong knowledge of SQL and NoSQL databases and experience in designing scalable data solutions.
9. Strong hands-on experience with GCP cloud services and architecture, including BigQuery, GCS, Pub/Sub, Dataflow, Dataproc, Cloud Run, and Workflows.
10. Strong understanding of distributed systems, event-driven architecture, scalability, high availability, and fault-tolerant system design.
11. Experience with Docker, Kubernetes, and CI/CD practices.
12. Experience in performance tuning and optimization of data pipelines and cloud-based data platforms.
13. Strong understanding of cloud security, data governance, access management, and best practices on GCP.
14. Excellent problem-solving, stakeholder management, technical leadership, and architecture decision-making skills.
15. Good-to-Have Skills:
16. Experience with Apache Flink, Airflow, Databricks, or Snowflake.
17. Experience with Terraform or other Infrastructure as Code (IaC) tools.
18. Exposure to AI/ML data pipelines, GenAI, or Agentic AI solutions.
19. Experience with observability and monitoring tools such as Cloud Monitoring, Prometheus, Grafana, ELK, or Splunk.
20. GCP Professional Cloud Architect or Professional Data Engineer certification.
21. Experience in mentoring teams and driving architecture standards, best practices, and governance.

Regard,

Vignesh

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