Designs and establishes secure and performant data architectures, enhancements, updates, and programming changes for portions and subsystems of data pipelines, repositories or models for structured/unstructured data.
Analyzes design and determines coding, programming, and integration activities required based on general objectives and knowledge of overall architecture of product or solution.
Writes and executes complete testing plans, protocols, and documentation for assigned portion of data system or component; identifies and debugs, and creates solutions for issues with code and integration into data system architecture.
Ability to manage and execute on an E2E data project from architecture inputs, to laying pipelines, data processing and dashboard building
Leads a project team of other data engineers to develop reliable, cost effective and high-quality solutions for assigned data system, model, or component.
Collaborates and communicates with project team regarding project progress and issue resolution.
Represents the data engineering team for all phases of larger and more-complex development projects.
Provides guidance and mentoring to less experienced staff members.
Qualifications:
4 - 6 years Data Engineer
Knowledge and Skills
Using data engineering tools, languages, frameworks to mine, cleanse and explore data.
Fluent in NoSQL & relational based systems.
Fluent in Databricks, Py spark and NodeJS
Fluent in complex, distributed and massively parallel systems.
Strong analytical and problem-solving skills with ability to represent complex algorithms in software.
Designing data systems/solutions to manage complex data.
Strong understanding of database technologies and management systems.
At least 1 year of exposure to working on AWS systems (Redshift and S3 must, Good to have EC2, lambda)
Fluency in Python and Linux shell scripting and small-scale server maintenance
Strong understanding of cloud-based systems/services.
Database architecture testing methodology, including execution of test plans, debugging, and testing scripts and tools.
Ability to Client pipelines across multiple systems is a key requirement
Familiarity with BI visualization tools, e.g. Looker, Power BI, Tableau
Behavioral Skills:
Ability to use a wide variety of open source technologies and tools
Excellent written and verbal communication skills; mastery in English and local language.
Ability to effectively communicate product architectures, design proposals and negotiate options at management levels
Collaborates with peers, junior engineers, data scientists and project team.
Typically interacts with high-level Individual Contributors, Managers and Program Teams.
Leads a project requiring data engineering solutions development
Education :
Bachelor’s or master’s degree in computer science, Information Systems, Engineering or equivalent.