Solutions Architect

Solutions Architect

Roles & Responsibilities:

• Design and implement scalable, cost-effective

  data pipelines on the AWS platform

  using services like S3, Athena, Glue, RDS, etc.
• Manage and optimize data storage strategies for efficient retrieval and integration with other applications.
• Support the ingestion and transformation of large datasets for reporting and analytics.
• Develop and maintain automation scripts using

  Python

  to streamline data processing workflows.
• Integrate tools and frameworks like

  PySpark

  to optimize performance and resource utilization.
• Implement monitoring and error-handling mechanisms to ensure reliability and scalability of data solutions.
• Work closely with onsite leads and client teams to gather and understand functional requirements.
• Collaborate with business stakeholders and the Data Science team to provide optimized datasets suitable for

  Business Reporting and AI/ML Exploration

  .
• Document processes, provide regular updates, and ensure transparency in deliverables.
• Optimize AWS service utilization to maintain cost-efficiency while meeting performance requirements.
• Provide insights on data usage trends and support the development of reporting dashboards for cloud costs.
• Ensure secure handling of sensitive data with encryption (e.g., AES-256, TLS) and role-based access control using AWS IAM.
• Maintain compliance with organizational and industry regulations for data solutions.

Skills Required:

• Strong emphasis on

  AWS platforms

  .
• Hands-on expertise with

  AWS services

  such as S3, Glue, Athena, RDS, etc.
• Proficiency in

  Python

  for building Data Pipelines for ingesting data and integrating it across applications.
• Strong proficiency in

  SQL

  .
• Demonstrated ability to design and develop scalable Data Pipelines and Workflows.
• Strong problem-solving skills and the ability to troubleshoot complex data issues.

Preferred Skills:

• Experience with

  Big Data technologies

  , including Spark, Kafka, and Scala, for Distributed Data processing.
• Hands-on expertise in working with

  AWS Big Data services

  such as EMR, DynamoDB, Athena, Glue, and MSK (Managed Streaming for Kafka).
• Familiarity with on-premises Big Data platforms and tools for Data Processing and Streaming.
• Proficiency in scheduling data workflows using

  Apache Airflow

  or similar orchestration tools like One Automation, Control-M, etc.
• Strong understanding of

  DevOps practices

  , including CI/CD pipelines and Automation Tools.
• Prior experience in the

  Telecommunications Domain

  , with a focus on large-scale data systems and workflows.
• AWS certifications (e.g., Solutions Architect, Data Analytics Specialty) are a plus.

QUALIFICATION:

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related technical field, or equivalent practical experience.