Data Platform Architect

Teliolabs Communication Private Limited

Key Responsibilities:

• Architect and Design scalable and secure data platforms, ensuring high availability and performance.
• Develop and Optimize data pipelines and ETL processes using modern frameworks and methodologies.
• Implement AI & ML Platforms, ensuring seamless integration with enterprise data ecosystems.
• Ensure Data Integrity & Governance by enforcing best practices for security, compliance, and quality.
• Oversee Data Migration strategies and execution from legacy to modern cloud-based architectures.
• Leverage AWS Services, including but not limited to S3, Redshift, Glue, EMR, Athena, Lambda, DynamoDB, and Kinesis.
• Lead Open Source Adoption, integrating tools like Apache Spark, Airflow, Kafka, and Flink for data processing.
• Collaborate with Cross-Functional Teams including Data Engineers, Data Scientists, and DevOps to streamline data workflows.
• Monitor Performance & Scalability, proactively addressing bottlenecks in data processing and analytics.
• Establish Best Practices for data modeling, schema design, and data architecture across various domains.
• Mentor and Guide engineering teams to enhance data capabilities within the organization.

Required Skills & Qualifications:

• 15+ years of experience in data engineering, data architecture, and cloud-based platforms.
• Expertise in AWS Cloud Services and hands-on experience with data storage, compute, and analytics tools.
• Strong ETL and Data Processing Knowledge, including batch and real-time data streaming.

Tools: Apache NiFi, Talend, Informatica PowerCenter, AWS Glue, Microsoft SSIS, Matillion, Fivetran, Stitch, dbt (data build tool)

• Proficiency in Open-Source Tools like Apache Spark, Hadoop, Airflow, Kafka, Flink, and Presto.
• Deep Understanding of AI & ML Workflows and their integration with data platforms.
• Proven Experience in Data Migration Strategies from on-premises to cloud.
• Expertise in Data Schema Design, Modeling, and Optimization for relational and NoSQL databases.
• Solid Programming Skills in Python, SQL, and Spark.
• Strong Problem-Solving Abilities with an analytical and strategic mindset.
• Excellent Leadership and Communication Skills, capable of working with technical and business stakeholders.

Preferred Qualifications:

• AWS Certified Solutions Architect or AWS Certified Data Analytics Certification.
• Experience working in AI-driven data platforms or MLOps environments.
• Familiarity with Kubernetes, Docker, and CI/CD pipelines for data workflows.