Technical Architect - Data Engineering (11:00 AM to 8 PM IST)

Technical Architect - Data Engineering (DE)

Overview

We are looking for a Technical Architect - Data Engineering (DE) who will provide strategic direction and broad oversight for our high-performing Data Engineering team that maintains, integrates and implements modern data engineering practices and technologies. This role requires a blend of architecture experience, executive polish, business sense, and especially technical depth. 

Requirements

• 8+ years of hands-on Experience with crafting and building large scale data pipelines in distributed environments with technologies such as Hadoop, Spark, Kafka, Hive etc.
• Experience with NoSQL datastores like Cassandra, Elasticsearch, HBase, MongoDB.
• Proven skills in designing, tuning & optimizing scalable, highly available distributed systems which can handle high data volumes.
• Strong understanding of software engineering principles and fundamentals including data structures and algorithms.
• Strong experience of working with API’s and integrating multiple applications together. 
• Proficient & hands-on in Python is a must.
• Good Experience with modern engineering practices and technologies including CICD, Cloud native development, social coding (github), chatbots and more.
• Good data modelling experience to address scale and read/write performance.
• Excellent written and oral communication skills on both technical and non-technical topics.
• Excellent general analytical & problem solving skills.
• Experience with cloud computing platform like AWS or GCP is a plus.

Educational Qualifications

Bachelor/Master’s degree in Computer Science, Computer Engineering, quantitative studies, such as Statistics, Math, Operation Research, Economics and Advanced Analytics

Key Responsibilities

Practice Development

• Work with DE Practice Lead and clients to understand business problems, industry context, data sources, potential risks, and constraints.
• Collaborate with Leadership – provide meaningful and credible feedback on Data Engineering capabilities, data availability, and customer trend information.
• Actively mentor and coach the team and help them realize the best solution to a problem 
• Facilitating, guiding, and influencing the clients and teams towards right information technology architecture and becoming interface between Business leadership, Tech leadership and the delivery teams
• Provide best practice advice to customers and team members