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Technical Architect - Data Engineering

No of Positions  No of Positions:   1

location Location: Hyderabad

date Tentative Start Date:   January 27, 2023

Work From Work From : Onsite

rate Rate : $ 12  -  20 (Hourly)

experience Experience : 8 to 10 Year

Job Applicants : 4
Job Views : 418
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Job Category : Information Technology & Services
Duration : 6-12  Month
Key Skills Required Skills
Python CICD AWS GCP Hadoop Spark Kafka NoSQL Technical Architect

Duration - Full-Time roles 

Location - This is an onsite opportunity in Hyderabad 

Shift timing - 11:00 AM to 8:00 PM IST

Note - Need stability at least 2 years of experience with each client. Do not send job hopper's profiles


Technical Architect - Data Engineering

This role requires a blend of architecture experience, executive polish, business sense, and especially


  • 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 platforms 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
  • Create an ecosystem that fosters innovation and encourages members of the CoE to build innovative solutions and publish papers/content in public domain.


Project Delivery

  • Lead our DE team performing standard-to-advanced and the highest complexity Data and API engineering in modern ways on modern platforms and technologies.
  • Works with and directs all resources on requirements and reviewing the quality of work prior to move to production.
  • Get the stakeholder feedback, get alignment on approaches, deliverables, and roadmaps.
  • Develop a project plan including milestones, dates, owners, and risks and contingency plans.
  • Create and maintain efficient data pipelines, often within clients’ architecture; typically, data are from a wide variety of sources, internal and external, and manipulated using SQL, spark, and Cloud big data technologies.
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