Lead Software Engineer (data Analytics) Job in Kpoint Technologies

Experience 5-10 years experience in working with large/web-scale data, data-driven business platforms, web analytics or data intelligence platforms.

Job Location Pune

Candidate Location Anywhere

Qualification Engineering Graduate BE, BTech or MCA

Relevant Industry Software and IT

Required Skill Set

• Experience in building, optimizing and scaling high-volume data pipelines using Apache Spark/Kafka/Hadoop or any other competing stacks.
• Experience of tools and techniques in data cleaning, scrubbing and de-duplication.
• Strong programming skills on one or more programming and scripting languages (Java, Python are preferred)
• Strong data background with sound fundamental understanding on data, relationships, aggregations, slicing/dicing.
• Demonstrable ability to mould and present data with crisp and appropriate visualizations to solve business problems.
• Strong understanding of Web/HTTP and nuances involved in delivering large datasets and visualizations over HTTP/s.
• Depth in working with, operationalizing and tuning at least one BigData/NoSQL store with sound understanding of scale out and performance characteristics.
• Experience with management of data stores to meet integrity, security and availability constraints.
• Should have been a part of significant end-to-end product deliveries.
• Sound communication skills with the ability to understand and speak business language when addressing data.
• Experience in building, optimizing and scaling high-volume data pipelines using Apache Spark/Kafka/Hadoop or any other competing stacks.
• Experience of tools and techniques in data cleaning, scrubbing and de-duplication.
• Strong programming skills on one or more programming and scripting languages (Java, Python are preferred)
• Strong data background with sound fundamental understanding on data, relationships, aggregations, slicing/dicing.
• Demonstrable ability to mould and present data with crisp and appropriate visualizations to solve business problems.
• Strong understanding of Web/HTTP and nuances involved in delivering large datasets and visualizations over HTTP/s.
• Depth in working with, operationalizing and tuning at least one BigData/NoSQL store with sound understanding of scale out and performance characteristics.
• Experience with management of data stores to meet integrity, security and availability constraints.
• Should have been a part of significant end-to-end product deliveries.
• Sound communication skills with the ability to understand and speak business language when addressing data.

Desired Skill Set

• Experience in implementing unit and integration test strategies for data pipeline and analytics following BDD/ATDD/TDD practices.
• Prior experience of cloud-based data services and AWS
• Has been a part of an agile team using standard CI/CD practices.
• Awareness in working with Linux-based Environments.
• Sound awareness of modeling API and REST conventions

Job Description / Responsibilities

• Desired Candidate will be a part of the Product Engineering team with specific focus on driving the roadmap of the analytics features for the next generation requirements.
• The engineer will get to work on:
  • On bleeding edge cloud video infrastructure
  • With real-world massive viewership data
  • To deliver to web scale
  • With a great team on an awesome product platform
• Will be responsible for complete delivery of the analytics roadmap ensuring:
  • Ability to scale to web-scale data
  • Data pipelines are efficient with low latency with increasing volumes
  • Usability is baked in with cutting edge testing and automation practices.
  • Rapid turnaround on analytics to ensure faster data-driven business decisions.
• Will drive the future analytics roadmap keeping track of industry standards and bleeding edge tools.
• Key aspect of the role is the ability to translate business intelligence requirements into data technology solutions and incorporate them as product features.
• Will be responsible for all aspects of management of the data stack including utilization, data security, availability, failover and disaster recovery.
• Will be on a sharp learning curve working on all aspects of the entire product stack.