āđ€āļ‡āļ·āđˆāļ­āļ™āđ„āļ‚āļāļēāļĢāļ„āđ‰āļ™āļŦāļē

āļ„āđ‰āļ™āļŦāļēāđ‚āļ”āļĒāđƒāļŠāđ‰āļ„āļģāļŦāļĨāļąāļ

āļ„āđ‰āļ™āļŦāļēāđ‚āļ”āļĒāļŦāļĄāļ§āļ”āļŦāļĄāļđāđˆāļ‡āļēāļ™

āđ€āļĨāļ·āļ­āļāļŦāļĄāļ§āļ”āļŦāļĄāļđāđˆāļ‡āļēāļ™

āļ„āđ‰āļ™āļŦāļēāđ‚āļ”āļĒāļ›āļĢāļ°āđ€āļ āļ—āļ˜āļļāļĢāļāļīāļˆ

āđ€āļĨāļ·āļ­āļāļ›āļĢāļ°āđ€āļ āļ—āļ˜āļļāļĢāļāļīāļˆ

āļ„āđ‰āļ™āļŦāļēāđ‚āļ”āļĒāļŠāđˆāļ§āļ‡āđ€āļ‡āļīāļ™āđ€āļ”āļ·āļ­āļ™

āļ•āļąāđ‰āļ‡āđāļ•āđˆ
āļ–āļķāļ‡

āļ„āđ‰āļ™āļŦāļēāđ‚āļ”āļĒāļŠāļ·āđˆāļ­āļšāļĢāļīāļĐāļąāļ—

āļžāļīāļĄāļžāđŒāļŠāļ·āđˆāļ­āļšāļĢāļīāļĐāļąāļ—

āļ„āđ‰āļ™āļŦāļēāđ‚āļ”āļĒāļĢāļ°āļ”āļąāļšāļ•āļģāđāļŦāļ™āđˆāļ‡āļ‡āļēāļ™

āļ„āđ‰āļ™āļŦāļēāđ‚āļ”āļĒāļ›āļĢāļ°āđ€āļ āļ—āļ‡āļēāļ™

āđāļŠāļ”āļ‡āļœāļĨ 1 - 10 āļ•āļģāđāļŦāļ™āđˆāļ‡āļ‡āļēāļ™ āļˆāļēāļāļ—āļąāđ‰āļ‡āļŦāļĄāļ” 10 āļ•āļģāđāļŦāļ™āđˆāļ‡āļ‡āļēāļ™
āļ—āļĩāđˆāļĄāļĩāļ„āļģāļ§āđˆāļē Hadoop
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āļ­āļąāļžāđ‚āļŦāļĨāļ”āđ€āļĢāļ‹āļđāđ€āļĄāđˆāļ‚āļ­āļ‡āļ„āļļāļ“ AI āļ‚āļ­āļ‡āđ€āļĢāļēāļˆāļ°āļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđāļĨāļ°āđāļ™āļ°āļ™āļģāļ•āļģāđāļŦāļ™āđˆāļ‡āļ‡āļēāļ™āļ—āļĩāđˆāļ”āļĩāļ—āļĩāđˆāļŠāļļāļ”āđƒāļŦāđ‰āļ„āļļāļ“
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļāļđāđ€āļāļīāļĨ āļ›āļĢāļ°āđ€āļ—āļĻāđ„āļ—āļĒ āļˆāļģāļāļąāļ” 1
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļāļđāđ€āļāļīāļĨ āļ›āļĢāļ°āđ€āļ—āļĻāđ„āļ—āļĒ āļˆāļģāļāļąāļ” 1
āļāļĢāļļāļ‡āđ€āļ—āļž, āļ‡āļēāļ™āļ‚āļēāļĒ ,āļšāļĢāļīāļŦāļēāļĢāļœāļĨāļīāļ•āļ āļąāļ“āļ‘āđŒ / āļšāļĢāļīāļŦāļēāļĢāđāļšāļĢāļ™āļ”āđŒāļŠāļīāļ™āļ„āđ‰āļē āļ‡āļēāļ™āļ‚āļēāļĒ,āļšāļĢāļīāļŦāļēāļĢāļœāļĨāļīāļ•āļ āļąāļ“āļ‘āđŒ / āļšāļĢāļīāļŦāļēāļĢāđāļšāļĢāļ™āļ”āđŒāļŠāļīāļ™āļ„āđ‰āļē

āļ—āļąāļāļĐāļ°:

Sales, Hadoop, ETL, English

āļ›āļĢāļ°āđ€āļ āļ—āļ‡āļēāļ™:

āļ‡āļēāļ™āļ›āļĢāļ°āļˆāļģ

āđ€āļ‡āļīāļ™āđ€āļ”āļ·āļ­āļ™:

āļŠāļēāļĄāļēāļĢāļ–āļ•āđˆāļ­āļĢāļ­āļ‡āđ„āļ”āđ‰

  • Bachelor's degree or equivalent practical experience.
  • 10 years of experience in software sales or account management.
  • Experience promoting analytics, data warehousing, or data management software.
6 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļ­āđ‚āļāļ”āđ‰āļē 2
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļ­āđ‚āļāļ”āđ‰āļē 2

āļ›āļĢāļ°āļŠāļšāļāļēāļĢāļ“āđŒ:

3 āļ›āļĩāļ‚āļķāđ‰āļ™āđ„āļ›

āļ—āļąāļāļĐāļ°:

Finance, SQL, Tableau

āļ›āļĢāļ°āđ€āļ āļ—āļ‡āļēāļ™:

āļ‡āļēāļ™āļ›āļĢāļ°āļˆāļģ

āđ€āļ‡āļīāļ™āđ€āļ”āļ·āļ­āļ™:

āļŠāļēāļĄāļēāļĢāļ–āļ•āđˆāļ­āļĢāļ­āļ‡āđ„āļ”āđ‰

  • Work closely with a diverse set of stakeholders in Finance and other parts of the organization.
  • Consult stakeholders to propose the best suited data solution.
  • Build end-to-end solutions including data workflows, dashboards, reports etc.
āļ§āļąāļ™āļ™āļĩāđ‰
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āđ€āļ­āļīāļ™āļŠāđŒāļ— āđāļ­āļ™āļ”āđŒ āļĒāļąāļ‡ 3
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āđ€āļ­āļīāļ™āļŠāđŒāļ— āđāļ­āļ™āļ”āđŒ āļĒāļąāļ‡ 3

āļ›āļĢāļ°āļŠāļšāļāļēāļĢāļ“āđŒ:

6 āļ›āļĩāļ‚āļķāđ‰āļ™āđ„āļ›

āļ—āļąāļāļĐāļ°:

Big Data, Good Communication Skills, Scala

āļ›āļĢāļ°āđ€āļ āļ—āļ‡āļēāļ™:

āļ‡āļēāļ™āļ›āļĢāļ°āļˆāļģ

āđ€āļ‡āļīāļ™āđ€āļ”āļ·āļ­āļ™:

āļŠāļēāļĄāļēāļĢāļ–āļ•āđˆāļ­āļĢāļ­āļ‡āđ„āļ”āđ‰

  • Collate technical and functional requirements through workshops with senior stakeholders in risk, actuarial, pricing and product teams.
  • Translate business requirements to technical solutions leveraging strong business acumen.
  • Analyse current business practice, processes, and procedures as well as identifying future business opportunities for leveraging Data & Analytics solutions on various platforms.
āļ§āļąāļ™āļ™āļĩāđ‰
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļ­āđ‚āļāļ”āđ‰āļē 4
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļ­āđ‚āļāļ”āđ‰āļē 4

āļ—āļąāļāļĐāļ°:

Big Data, Research, Statistics

āļ›āļĢāļ°āđ€āļ āļ—āļ‡āļēāļ™:

āļ‡āļēāļ™āļ›āļĢāļ°āļˆāļģ

āđ€āļ‡āļīāļ™āđ€āļ”āļ·āļ­āļ™:

āļŠāļēāļĄāļēāļĢāļ–āļ•āđˆāļ­āļĢāļ­āļ‡āđ„āļ”āđ‰

  • Design, code, experiment and implement models and algorithms to maximize customer experience, supply side value, business outcomes, and infrastructure readiness.
  • Mine a big data of hundreds of millions of customers and more than 600M daily user generated events, supplier and pricing data, and discover actionable insights to drive improvements and innovation.
  • Work with developers and a variety of business owners to deliver daily results with the best quality.
2 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āđ€āļ­āļīāļ™āļŠāđŒāļ— āđāļ­āļ™āļ”āđŒ āļĒāļąāļ‡ 5
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āđ€āļ­āļīāļ™āļŠāđŒāļ— āđāļ­āļ™āļ”āđŒ āļĒāļąāļ‡ 5

āļ›āļĢāļ°āļŠāļšāļāļēāļĢāļ“āđŒ:

2 āļ›āļĩāļ‚āļķāđ‰āļ™āđ„āļ›

āļ—āļąāļāļĐāļ°:

Big Data, Good Communication Skills, Scala

āļ›āļĢāļ°āđ€āļ āļ—āļ‡āļēāļ™:

āļ‡āļēāļ™āļ›āļĢāļ°āļˆāļģ

āđ€āļ‡āļīāļ™āđ€āļ”āļ·āļ­āļ™:

āļŠāļēāļĄāļēāļĢāļ–āļ•āđˆāļ­āļĢāļ­āļ‡āđ„āļ”āđ‰

  • You will be involved in all aspects of the project life cycle, including strategy, road-mapping, architecture, implementation and development.
  • You will work with business and technical stakeholders to gather and analyse business requirements to convert them into the technical requirements, specifications, mapping documents.
  • You will collaborate with technical teams, making sure the newly implemented solutions/technology are meeting business requirements.
4 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āđ„āļ—āļĒāļ­āļ­āļĒāļĨāđŒ 6
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āđ„āļ—āļĒāļ­āļ­āļĒāļĨāđŒ 6
āļĻāļĢāļĩāļĢāļēāļŠāļē, āļŠāļĨāļšāļļāļĢāļĩ, āļšāļĢāļīāļŦāļēāļĢāļœāļĨāļīāļ•āļ āļąāļ“āļ‘āđŒ / āļšāļĢāļīāļŦāļēāļĢāđāļšāļĢāļ™āļ”āđŒāļŠāļīāļ™āļ„āđ‰āļē āļšāļĢāļīāļŦāļēāļĢāļœāļĨāļīāļ•āļ āļąāļ“āļ‘āđŒ / āļšāļĢāļīāļŦāļēāļĢāđāļšāļĢāļ™āļ”āđŒāļŠāļīāļ™āļ„āđ‰āļē

āļ›āļĢāļ°āļŠāļšāļāļēāļĢāļ“āđŒ:

5 āļ›āļĩāļ‚āļķāđ‰āļ™āđ„āļ›

āļ—āļąāļāļĐāļ°:

Data Analysis, Automation, Python

āļ›āļĢāļ°āđ€āļ āļ—āļ‡āļēāļ™:

āļ‡āļēāļ™āļ›āļĢāļ°āļˆāļģ

āđ€āļ‡āļīāļ™āđ€āļ”āļ·āļ­āļ™:

āļŠāļēāļĄāļēāļĢāļ–āļ•āđˆāļ­āļĢāļ­āļ‡āđ„āļ”āđ‰

  • Work with stakeholders throughout the organization to understand data needs, identify issues or opportunities for leveraging company data to propose solutions for support decision making to drive business solutions.
  • Adopting new technology, techniques, and methods such as machine learning or statistical techniques to produce new solutions to problems.
  • Conducts advanced data analysis and create the appropriate algorithm to solve analytics problems.
5 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļ­āđ‚āļāļ”āđ‰āļē 7
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļ­āđ‚āļāļ”āđ‰āļē 7

āļ—āļąāļāļĐāļ°:

Big Data, Research, Statistics

āļ›āļĢāļ°āđ€āļ āļ—āļ‡āļēāļ™:

āļ‡āļēāļ™āļ›āļĢāļ°āļˆāļģ

āđ€āļ‡āļīāļ™āđ€āļ”āļ·āļ­āļ™:

āļŠāļēāļĄāļēāļĢāļ–āļ•āđˆāļ­āļĢāļ­āļ‡āđ„āļ”āđ‰

  • Design, code, experiment and implement models and algorithms to maximize customer experience, supply side value, business outcomes, and infrastructure readiness.
  • Mine a big data of hundreds of millions of customers and more than 600M daily user generated events, supplier and pricing data, and discover actionable insights to drive improvements and innovation.
  • Work with developers and a variety of business owners to deliver daily results with the best quality.
9 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļšāļĢāļīāļĐāļąāļ— āļ‹āļĩāļžāļĩ āđāļ­āđ‡āļāļ‹āđŒāļ•āļĢāđ‰āļē āļˆāļģāļāļąāļ” āļĄāļŦāļēāļŠāļ™ āđāļĄāđ‡āļ„āđ‚āļ„āļĢ 8
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļšāļĢāļīāļĐāļąāļ— āļ‹āļĩāļžāļĩ āđāļ­āđ‡āļāļ‹āđŒāļ•āļĢāđ‰āļē āļˆāļģāļāļąāļ” āļĄāļŦāļēāļŠāļ™ āđāļĄāđ‡āļ„āđ‚āļ„āļĢ 8

āļ—āļąāļāļĐāļ°:

ETL, Python, Java

āļ›āļĢāļ°āđ€āļ āļ—āļ‡āļēāļ™:

āļ‡āļēāļ™āļ›āļĢāļ°āļˆāļģ

āđ€āļ‡āļīāļ™āđ€āļ”āļ·āļ­āļ™:

āļŠāļēāļĄāļēāļĢāļ–āļ•āđˆāļ­āļĢāļ­āļ‡āđ„āļ”āđ‰

  • Design, develop, and maintain scalable data pipelines and ETL processes.
  • Implement and optimize data storage solutions, including data warehouses and data lakes.
  • Collaborate with data scientists and analysts to understand data requirements and provide efficient data access.
1 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļžāļĩāļ—āļĩāļˆāļĩ 9
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļžāļĩāļ—āļĩāļˆāļĩ 9

āļ—āļąāļāļĐāļ°:

ETL, SQL, Data Analysis

āļ›āļĢāļ°āđ€āļ āļ—āļ‡āļēāļ™:

āļ‡āļēāļ™āļ›āļĢāļ°āļˆāļģ

āđ€āļ‡āļīāļ™āđ€āļ”āļ·āļ­āļ™:

āļŠāļēāļĄāļēāļĢāļ–āļ•āđˆāļ­āļĢāļ­āļ‡āđ„āļ”āđ‰

  • Data Pipeline Development: Create and maintain optimal data pipeline architecture.
  • Data Integration: Assemble large, complex data sets that meet functional and non-functional business requirements.
  • Process Improvement: Identify, design, and implement internal process improvements, such as automating manual processes and optimizing data delivery.
10 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļšāļīāđŠāļāļ‹āļĩ 10
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļšāļīāđŠāļāļ‹āļĩ 10

āļ—āļąāļāļĐāļ°:

Data Analysis, ETL, Data Warehousing

āļ›āļĢāļ°āđ€āļ āļ—āļ‡āļēāļ™:

āļ‡āļēāļ™āļ›āļĢāļ°āļˆāļģ

āđ€āļ‡āļīāļ™āđ€āļ”āļ·āļ­āļ™:

āļŠāļēāļĄāļēāļĢāļ–āļ•āđˆāļ­āļĢāļ­āļ‡āđ„āļ”āđ‰

  • Data Architecture: Design, develop, and maintain the overall data architecture and data pipeline systems to ensure efficient data flow and accessibility for analytical purposes.
  • Data Integration: Integrate data from multiple sources, including point-of-sale systems, customer databases, e-commerce platforms, supply chain systems, and other relevant data sources, ensuring data quality and consistency.
  • Data Modeling: Design and implement data models that are optimized for scalability, ...
23 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
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āļ­āļąāļžāđ‚āļŦāļĨāļ”āđ€āļĢāļ‹āļđāđ€āļĄāđˆāļ‚āļ­āļ‡āļ„āļļāļ“ AI āļ‚āļ­āļ‡āđ€āļĢāļēāļˆāļ°āļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđāļĨāļ°āđāļ™āļ°āļ™āļģāļ•āļģāđāļŦāļ™āđˆāļ‡āļ‡āļēāļ™āļ—āļĩāđˆāļ”āļĩāļ—āļĩāđˆāļŠāļļāļ”āđƒāļŦāđ‰āļ„āļļāļ“
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āļĨāļ‡āļ—āļ°āđ€āļšāļĩāļĒāļ™āļāļąāļš WorkVenture āđ€āļžāļ·āđˆāļ­āļ„āđ‰āļ™āļŦāļēāļ‡āļēāļ™āđƒāļŦāļĄāđˆāļĨāđˆāļēāļŠāļļāļ”āđāļĨāļ°āļ­āđˆāļēāļ™āļĢāļĩāļ§āļīāļ§āļšāļĢāļīāļĐāļąāļ—āļˆāļēāļāļœāļđāđ‰āļ—āļģāļ‡āļēāļ™āļˆāļĢāļīāļ‡