IN-Director Senior Data Architect Data & Analytics

1. Design and implement endtoend data pipelines using cloudbased services (AWS/ GCP/Azure) and conventional data processing frameworks.
2. Lead the development of data architecture, ensuring scalability, security, and performance.
3. Collaborate with crossfunctional teams, including DevOps, to design and implement data lakes, data warehouses, and data ingestion/extraction processes.
4. Develop and optimize data processing workflows using PySpark, Kafka, and other big data processing frameworks.
5. Ensure data quality, integrity, and security across all data pipelines and architectures.
6. Provide technical leadership and guidance to junior team members.
7. Design and implement data load strategies, data partitioning, and data storage solutions.
8. Collaborate with stakeholders to understand business requirements and develop data solutions to meet those needs.
9. Work closely with DevOps team to ensure seamless integration of data pipelines with overall system architecture.
10. Participate in design and implementation of CI/CD pipelines for data workflows.

DevOps Requirements

1. Knowledge of DevOps practices and tools, such as Jenkins, GitLab CI/CD, or Apache Airflow.

2. Experience with containerization using Docker.

3. Understanding of infrastructure as code (IaC) concepts using tools like Terraform or AWS CloudFormation.

4. Familiarity with monitoring and logging tools, such as Prometheus, Grafana, or ELK Stack.

Requirements

1. 12-14 years of experience for Senior Data Architect

in data architecture, data warehousing, and big data processing.
2. Strong expertise in cloudbased technologies (AWS/ GCP/ Azure) and data processing frameworks (PySpark, Kafka, Flink , Beam etc.).
3. Experience with data ingestion, data extraction, data warehousing, and data lakes.
4. Strong understanding of performance optimization, data partitioning, and data storage solutions.
5. Excellent leadership and communication skills.
6. Experience with NoSQL databases is a plus.

Mandatory skill sets

1. Experience with agile development methodologies.
2. Certification in cloudbased technologies (AWS / GCP/ Azure) or data processing frameworks.
3. Experience with data governance, data quality, and data security.

Preferred skill sets

Knowledge of AgenticAI and GenAI is added advantage