Architect – Big Data and Data Science

Designing and Architecture enterprise-grade technical solutions to a wide range of business domains providing technical know-how and hands-on expertise in the areas of Big Data, Data Engineering, Machine Learning and Data Science.

Key Job Responsibilities/Tasks

  • Build, maintain and monitor CI/CD pipeline and all deployments up to production
  • Make clear, robust, and technically sound design decisions
  • Build technically strong, quality-oriented engineering teams and groom junior-level associates to their next level
  • Review and approve technology/designs developed by the engineering team
  • Maintain proper documentation related to system development and design decisions taken and rationale behind the decisions for all projects/solutions and guide Tech Leads to enforce all junior associates to maintain up-to-date documentation
  • Provide Internal / external review & consultancy on technical standards, including platforms, tools, coding standards, etc.
  • Involve in initial project meetings and system specification review process to check the technical feasibility
  • Actively participate in all stages of the software development lifecycle
  • Work collaboratively in multiple cross-functional teams/disciplines
  • Drive POC, POT, R&D tasks
  • Define the optimal higher-level architecture to meet client requirements & convince the stakeholders
  • Inspire, mentor, and encourage associates to intelligently apply the industry best practices with the right customizations
  • Define quantifiable objectives that encapsulate quality attributes to measure non-functional requirements such as performance, security, scalability, etc.
  • Provide accurate estimations for various elements of projects, components, etc.
  • Engage in defining and driving corporate technical vision/road-map aligning with global technology trends and standards
  • Contribute to the project and corporate level knowledge-sharing initiatives
  • Working closely with the project team having efficient and effective communication & open attitude
  • Identify and encourage team members to reuse organizational reusable software components while contributing to reusable repositories
  • Involve in presale activities such as client discussions, project scoping/estimations, SOW/RFP preparations

Minimum Qualifications

  • Minimum 12+ years of industry experience building production grade technical solutions
  • Minimum of 5+ years of experience in Designing and Architecture
  • Thorough understanding in the areas of Big Data, Data Engineering, Machine Learning, Artificial Intelligence and Data Science concepts
  • Hands on experience in Big Data, Data Engineering, Machine Learning and Data Science model building
  • Expert knowledge in Distributed Processing, Distributed File Systems, Data Warehousing, Batch and Real time processing as well as common Data Science algorithms
  • Expertise on major cloud platforms such as AWS, GCP and Azure

Experience and Skill Requirement

  • Programming Languages: Java, Scala, Python, R
  • Big Data Frameworks: Hadoop, HDP, Databricks
  • Data Engineering Techniques: Data Ingession, ETL, Data Lake, Data Wearhouse, BI & Reporting
  • Big Data & Data Engineering Tools: Apache Spark, Kafka, Apache Storm, Flink, Talend, ELK
  • Data Science: Exploratory Data Analysis, Feature Engineering, Model Creation, Auto ML pipeline building, Hyper Parameter Tuning, Model Deployment
  • Cloud Platforms and Technologies: GCP (Data Proc, Big Table, Big Query, Cloud Storage), AWS (EMR, RDS, Redshift, S3, EC2, EKS) and Azure
  • Database: Hive, HBase, Mongo DB, PostgreSql, Oracle, MS SQL Server, MySQL
  • Build Tools: Maven, Ant, Gradle
  • Workflow Orchestration: Azkaban, Airflow
  • CICD Pipeline: Jenkins, Nexus
  • Development Methodologies: Agile/Scrum, Waterfall
  • Design: Object Oriented Programming, Design Patterns, Database Modelling, UML Modeling, C4 Modelling

    Upload Your CV [ Please limit file size to 5 MB ]

    zone24x7 Logo
    ISO-2700 Logo
    GoodFirms Badge
    GoodFirms Badge
    • USA
    • Sri Lanka
    • UK