SDE 2 - Python PySpark SQL

Sigmoid Data Engineering

Bengaluru

On-site

INR 800,000 - 1,500,000

Full time

14 days+

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Job summary

Sigmoid Data Engineering in Bengaluru seeks a skilled professional to build scalable applications and support clients, including Fortune 500 companies. The role emphasizes technical leadership and developing distributed components using Java or Python, and requires 3-5 years of experience in relevant fields.

The ideal candidate should have hands-on knowledge in big data technologies and demonstrate effective communication skills to collaborate with diverse teams.

Qualifications

  • 3-5 years of relevant work experience in software development.
  • Experience in developing enterprise-scale applications and frameworks.
  • Hands-on knowledge of big data technologies like Map Reduce and Hadoop.
  • Effective communication skills and collaboration aptitude.

Responsibilities

  • Align Sigmoid with key client strategic initiatives.
  • Develop scalable and fault-tolerant distributed components.
  • Provide technical leadership and manage day-to-day operations.
  • Design and implement APIs and integration patterns.

Skills

Java
Python
Map Reduce
Hadoop
PySpark
Hbase
ElasticSearch
SQL

Education

Bachelor's in Computer Science or related field

Tools

Big Data technologies
Database modeling and development

Job description

You will be responsible for building a highly‑scalable and extensible robust application. This position reports to the Engineering Manager.

Responsibilities
  • Align Sigmoid with key Client initiatives
  • Interface daily with customers across leading Fortune 500 companies to understand strategic requirements
  • Ability to understand business requirements and tie them to technology solutions
  • Open to work from client location as per the demand of the project / customer.
  • Facilitate in Technical Aspects
  • Develop and evolve highly scalable and fault‑tolerant distributed components using Java technologies.
  • Excellent experience in Application development and support, integration development and quality assurance.
  • Provide technical leadership and manage it day to day basis
  • Stay up‑to‑date on the latest technology to ensure the greatest ROI for customer & Sigmoid
  • Hands on coder with good understanding on enterprise level code.
  • Design and implement APIs, abstractions and integration patterns to solve challenging distributed computing problems
  • Experience in defining technical requirements, data extraction, data transformation, automating jobs, productionizing jobs, and exploring new big data technologies within a Parallel Processing environment
  • Culture: Must be a strategic thinker with the ability to think unconventional / out:of:box.
  • Analytical and solution driven orientation.
  • Raw intellect, talent and energy are critical.
  • Entrepreneurial and Agile: understands the demands of a private, high growth company.
  • Ability to be both a leader and hands on "doer".
Qualifications
  • 3-5 year track record of relevant work experience and a computer Science or a related technical discipline is required
  • Experience in development of Enterprise scale applications and capable in developing framework, design patterns etc. Should be able to understand and tackle technical challenges, and propose comprehensive solutions.
  • Experience with functional and object‑oriented programming, Java (Preferred) or Python is a must.
  • Hand‑On knowledge in Map Reduce, Hadoop, PySpark, Hbase and ElasticSearch.
  • Development and support experience in Big Data domain
  • Experience with database modelling and development, data mining and warehousing.
  • Unit, Integration and User Acceptance Testing.
  • Effective communication skills (both written and verbal)
  • Ability to collaborate with a diverse set of engineers, data scientists and product managers
  • Comfort in a fast‑paced start‑up environment.
Preferred Qualification
  • Experience in Agile methodology.
  • Proficient with SQL and its variation among popular databases.
  • Experience working with large, complex data sets from a variety of sources.
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