Key Responsibilities

- Design and implement enterprise-scale Big Data and Data Lake architectures.
- Develop scalable, secure, and high-performance data platforms using cloud-native services.
- Define architecture standards, data models, frameworks, and best practices.
- Lead the design of batch and real-time data processing pipelines.
- Architect ETL/ELT frameworks for structured, semi-structured, and unstructured data.
- Optimize data storage, partitioning, indexing, and query performance.
- Design and implement Data Lake, Data Warehouse, and Lakehouse solutions.
- Collaborate with business teams to understand analytics and reporting requirements.
- Ensure data quality, security, governance, and compliance across the data ecosystem.
- Work with DevOps teams to implement CI/CD pipelines and Infrastructure as Code.
- Mentor technical teams and provide architectural guidance.
- Conduct architecture reviews, proof of concepts (POCs), and technology evaluations.
- Troubleshoot complex production issues and recommend performance improvements.

Mandatory Technical Skills

Big Data Technologies

- Hadoop Ecosystem
- Apache Spark
- Apache Kafka
- Apache Hive
- Apache HBase
- Apache Airflow
- Apache NiFi
- Apache Flink (Preferred)

Cloud Platforms

- Microsoft Azure
- AWS
- Google Cloud Platform (Preferred)

Azure Services

- Azure Data Factory (ADF)
- Azure Synapse Analytics
- Azure Databricks
- Azure Data Lake Storage (ADLS)
- Azure Event Hub
- Azure Functions
- Azure Kubernetes Service (AKS)
- Azure Monitor

Programming

- Python
- Scala
- Java
- SQL
- Shell Scripting

Databases

- SQL Server
- PostgreSQL
- Oracle
- MongoDB
- Cassandra
- Snowflake

Data Engineering

- ETL/ELT Design
- Data Lake Architecture
- Data Warehouse
- Data Modeling
- Data Migration
- Data Integration




- Metadata Management

DevOps & Automation

- Azure DevOps
- Git
- GitHub
- Jenkins
- Docker
- Kubernetes
- Terraform
- ARM Templates / Bicep
- CI/CD Pipelines

Required Skills

- Strong knowledge of distributed computing architecture.
- Hands-on experience with batch and streaming data pipelines.
- Experience designing cloud-native data platforms.
- Expertise in data governance, security, and compliance.
- Solid understanding of performance tuning and scalability.
- Experience with API integrations and microservices architecture.
- Excellent analytical and problem-solving skills.
- Strong stakeholder management and communication skills.
- Experience leading architecture discussions and mentoring engineering teams.

Preferred Certifications

- Microsoft Certified: Azure Solutions Architect Expert
- Microsoft Certified: Azure Data Engineer Associate
- Databricks Certified Data Engineer
- AWS Certified Solutions Architect – Professional
- Google Professional Data Engineer
- TOGAF Certification (Preferred)

Education

- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.

Preferred Candidate Profile

- 10–15 years of overall IT experience with at least 5 years in Big Data Architecture.
- Proven experience designing enterprise-scale data platforms.
- Strong exposure to cloud migration and modernization projects.
- Experience in Banking, Healthcare, Telecom, Retail, or BFSI domains is an advantage.
- Excellent leadership, client-facing, and presentation skills.
- Stable career history with the ability to lead cross-functional teams.
- Candidates available to join immediately or within 30 days will be preferred.

Pay: ₹1,500,000.00 - ₹4,200,000.00 per year

Work Location: Remote

📌 Big Data Architect (India)
🏢 TalentNest Solutions
📍 India