Data Architect
1 day ago
**Job Information**:
Work Experience: 15+ years
Industry: IT Services
**Job Type**: FULL TIME
Location: Chennai, India
**Role Overview**:
**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.
**Why Join Us?**:
- Work with cutting-edge technologies in data and AI.
- Influence key architectural decisions and drive innovation.
- Competitive compensation and benefits package.
- A collaborative and high-performing team environment.
**Interview Process**:
- Technical Assessment
- Technical Round 1
- Technical Round 2
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