Associate Solutions Architect

3 weeks ago

Chennai, India TivonaGlobal Technologies Full time

The Associate Solution Architect will be responsible for providing technical leadership, architecture, governance, and oversight of our next generation of data processing software using a modern cloud-native technology stack with Python on AWS cloud infrastructure. This is a rare opportunity to make a big impact on both the team and the organization by being part of the design and development of application frameworks 


The ideal candidate has a passion for solving business problems with technology and can effectively communicate business and technical needs to stakeholders.


Please send in your resumes to careers@tivonaglobal.com


Key Responsibilities


  • Requirement Analysis: Collaborate with stakeholders to understand business requirements and data sources, and define the architecture and design of data pipelines to meet these requirements.
  • Architecture Design: Design scalable, reliable, and efficient data pipelines to ingest, process, transform, and store large volumes of data from diverse sources, ensuring data quality and consistency.
  • Technology Selection: Evaluate using POCs and recommend appropriate technologies, frameworks, and tools for building and managing data pipelines, considering factors like performance, scalability, and cost-effectiveness.
  • Data Processing: Develop and implement data processing logic, including data cleansing, transformation, and aggregation, using technologies like AWS Glue, Batch, Lambda.
  • Data Storage: Design and implement data storage solutions, including data lakes, data warehouses, and NoSQL databases, to store and manage data for analysis and reporting.
  • Data Integration: Integrate data pipelines with external systems, APIs, and services to automate data workflows and ensure seamless data exchange between systems.
  • Monitoring and Logging: Implement monitoring and logging solutions for data pipelines using tools like AWS CloudWatch to ensure data pipeline health and performance.
  • Security and Compliance: Ensure data pipeline architecture complies with security best practices and regulatory requirements, implementing encryption, access controls, and data masking as needed.
  • Documentation: Create and maintain documentation for data pipeline architecture, design, and implementation, including diagrams, data flow descriptions, and operational procedures.
  • Collaboration: Collaborate with cross-functional teams, including data engineers, data scientists, and business analysts, to understand their requirements and integrate data pipelines into their workflows.
  • Continuous Improvement: Stay updated with the latest trends, tools, and technologies in data engineering and data pipeline architecture, and continuously improve data pipeline processes and methodologies.


Desired Skills & Requirement


  • Data Engineering: Understanding of data engineering concepts and principles, including data ingestion, processing, transformation, and storage, using tools and technologies such as AWS Glue, Batch, Lambda.
  • Data Modeling: Knowledge of data modeling techniques and best practices for designing efficient and scalable data pipelines, including dimensional modeling, star schemas, and snowflake schemas.
  • Programming Languages: Proficiency in programming languages commonly used in data engineering, such as Python, Java, or Scala, as well as experience with SQL for data querying and manipulation.
  • Cloud Computing: Proficiency in using AWS cloud services for data pipeline architecture and implementation.
  • Data Integration: Understanding of data integration techniques and tools for integrating data from various sources, including batch and real-time data integration, and experience with ETL (Extract, Transform, Load) processes.
  • Database Systems: Knowledge of database systems, including relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra), and experience in designing and managing database schemas.
  • Data Governance: Awareness of data governance principles and practices, including data quality, data lineage, and data privacy, and ability to ensure compliance with relevant regulations and standards.
  • Problem-solving Skills: Excellent problem-solving skills, with the ability to analyze complex data pipeline requirements and design solutions that meet business needs.
  • Communication and Collaboration: Strong communication and collaboration skills, with the ability to effectively communicate technical concepts to non-technical stakeholders and work effectively in a team environment.
  • Learning Agility: A commitment to continuous learning and staying updated with the latest trends, tools, and technologies in data engineering and data pipeline architecture.


Academic Qualification and Industry Experience


  • Bachelor's Degree: A bachelor's degree in Computer Science, Software Engineering, or a related field is often preferred, although equivalent experience and certifications can also be valuable. Experience with Financial domain knowledge is a plus.
  • At least 7 years of experience in solutions architecture, software development, or any other related field.

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