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™

BPTW Banner
āđāļŠāļ”āļ‡āļœāļĨ 1 - 13 āļ•āļģāđāļŦāļ™āđˆāļ‡āļ‡āļēāļ™ āļˆāļēāļāļ—āļąāđ‰āļ‡āļŦāļĄāļ” 13 āļ•āļģāđāļŦāļ™āđˆāļ‡āļ‡āļēāļ™
āļ—āļĩāđˆāļĄāļĩāļ„āļģāļ§āđˆāļē ETL
Upload ResumeUpload Resume
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™ āđ‚āļ­āļŠāļ–āļŠāļ āļē 1
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āđ‚āļ­āļŠāļ–āļŠāļ āļē 1
āļšāļēāļ‡āļāļ°āļ›āļī, āļāļĢāļļāļ‡āđ€āļ—āļž, āđ„āļ­āļ—āļĩ / āđ€āļ‚āļĩāļĒāļ™āđ‚āļ›āļĢāđāļāļĢāļĄ āđ„āļ­āļ—āļĩ / āđ€āļ‚āļĩāļĒāļ™āđ‚āļ›āļĢāđāļāļĢāļĄ

āļ—āļąāļāļĐāļ°:

ETL, Compliance, SQL

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, implement, and manage end-to-end data pipelines architectures.
  • Configure and maintain data ingest workflows (ETL) across several production systems.
  • Transform data into Data Mart, Data Model that can be easily analyzed.
āļ§āļąāļ™āļ™āļĩāđ‰
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ Amaris Consulting Bangkok 2
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ Amaris Consulting Bangkok 2
āļāļĢāļļāļ‡āđ€āļ—āļž,

āļ›āļĢāļ°āļŠāļšāļāļēāļĢāļ“āđŒ:

2 āļ›āļĩāļ‚āļķāđ‰āļ™āđ„āļ›

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‰

  • Your missions
  • Develop and maintain data ingestion pipelines from multiple data sources
  • Support the design and execution of ETL/ELT processes
1 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļāļĢāļļāļ‡āđ„āļ—āļĒ 3
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļāļĢāļļāļ‡āđ„āļ—āļĒ 3

āļ—āļąāļāļĐāļ°:

ETL, Big Data

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‰

  • Pipeline Development: Support the design and maintenance of scalable ETL/ELT pipelines for structured and unstructured datasets..
  • AI Data Readiness: Assist in building data ingestion flows for Vector Databases and supporting RAG (Retrieval-Augmented Generation) architectures..
  • Data Modeling: Contribute to the creation of robust data models and Feature Stores that serve both traditional analytics and machine learning workloads..
āļ§āļąāļ™āļ™āļĩāđ‰
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ LSEG London Stock Exchange Group 4
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ LSEG London Stock Exchange Group 4
āļāļĢāļļāļ‡āđ€āļ—āļž, āļāļēāļĢāļˆāļąāļ”āļāļēāļĢ ,āđ„āļ­āļ—āļĩ / āđ€āļ‚āļĩāļĒāļ™āđ‚āļ›āļĢāđāļāļĢāļĄ ,āļ™āļąāļāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒ āļāļēāļĢāļˆāļąāļ”āļāļēāļĢ,āđ„āļ­āļ—āļĩ / āđ€āļ‚āļĩāļĒāļ™āđ‚āļ›āļĢāđāļāļĢāļĄ,āļ™āļąāļāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒ

āļ›āļĢāļ°āļŠāļšāļāļēāļĢāļ“āđŒ:

8 āļ›āļĩāļ‚āļķāđ‰āļ™āđ„āļ›

āļ—āļąāļāļĐāļ°:

ETL, Automation, Scrum, 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‰

  • Lead and strengthen a team of data analysts - fostering high performance, collaboration, and professional development.
  • Own the data product - oversee the design, development, and maintenance of dashboards, data models, and reporting frameworks that provide visibility into IT assets and infrastructure.
  • Build scalable data solutions - drive the implementation of ETL pipelines, automation, and data integrity practices.
1 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļ˜āļ™āļēāļ„āļēāļĢāļāļĢāļļāļ‡āļĻāļĢāļĩ 5
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļ˜āļ™āļēāļ„āļēāļĢāļāļĢāļļāļ‡āļĻāļĢāļĩ 5
āļĒāļēāļ™āļ™āļēāļ§āļē, āļāļĢāļļāļ‡āđ€āļ—āļž, āđ„āļ­āļ—āļĩ / āđ€āļ‚āļĩāļĒāļ™āđ‚āļ›āļĢāđāļāļĢāļĄ ,āļ™āļąāļāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒ āđ„āļ­āļ—āļĩ / āđ€āļ‚āļĩāļĒāļ™āđ‚āļ›āļĢāđāļāļĢāļĄ,āļ™āļąāļāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒ

āļ—āļąāļāļĐāļ°:

ETL, Assurance, Automation

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‰

  • Analyze business, risk, and regulatory requirements and translate them into system architecture, data models, and ETL designs.
  • Design and implement data integration solutions to support Reporting platforms - Perform and oversee data transformation, validation, reconciliation, and data quality assurance to ensure accuracy and regulatory compliance.
  • Design, develop, and maintain automation and monitoring scripts using Shell scripts and Batch scripts - Develop, maintain, and optimize PL/SQL objects on Oracle databas ...
āļ§āļąāļ™āļ™āļĩāđ‰
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļāļĢāļļāļ‡āđ„āļ—āļĒ 6
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļāļĢāļļāļ‡āđ„āļ—āļĒ 6

āļ—āļąāļāļĐāļ°:

SQL, Oracle, 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‰

  • Bachelor s degree in computer science, Information Systems, Engineering, or a related field.
  • At least 3 years of experience as a Data Engineer or in a related role.
  • Hands-on experience with SQL, database management (e.g., Oracle, SQL Server, PostgreSQL), and data warehousing concepts.
āļ§āļąāļ™āļ™āļĩāđ‰
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļšāļēāļ‡āļˆāļēāļ 7
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļšāļēāļ‡āļˆāļēāļ 7

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‰

  • The Senior Data Engineer position plays a key role in designing, developing, and managing cloud-based data platforms, as well as creating data structures for high-level data analysis, and works with business and technical teams to ensure that data management is appropriate and supports organizational goals.
  • Responsible for the design, construction, and maintenance of optimal and scalable data pipeline architectures on cloud platforms (e.g., GCP, AWS, Azure).
  • Oversee the development and management of complex ETL/ELT processes for data ingesti ...
āļ§āļąāļ™āļ™āļĩāđ‰
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ Amaris Consulting Bangkok 8
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ Amaris Consulting Bangkok 8
āļāļĢāļļāļ‡āđ€āļ—āļž, āđ„āļ­āļ—āļĩ / āđ€āļ‚āļĩāļĒāļ™āđ‚āļ›āļĢāđāļāļĢāļĄ ,āļ™āļąāļāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒ āđ„āļ­āļ—āļĩ / āđ€āļ‚āļĩāļĒāļ™āđ‚āļ›āļĢāđāļāļĢāļĄ,āļ™āļąāļāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒ

āļ›āļĢāļ°āļŠāļšāļāļēāļĢāļ“āđŒ:

3 āļ›āļĩāļ‚āļķāđ‰āļ™āđ„āļ›

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‰

  • Support and maintain monthly ETL processes for actuarial data workflows.
  • Provide technical support for Actuarial and Reinsurance teams.
  • Develop, modify, and maintain stored procedures, SQL scripts, and SSIS packages.
14 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ NTT Thailand 9
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ NTT Thailand 9
āļāļĢāļļāļ‡āđ€āļ—āļž, āđ„āļ­āļ—āļĩ / āđ€āļ‚āļĩāļĒāļ™āđ‚āļ›āļĢāđāļāļĢāļĄ āđ„āļ­āļ—āļĩ / āđ€āļ‚āļĩāļĒāļ™āđ‚āļ›āļĢāđāļāļĢāļĄ

āļ›āļĢāļ°āļŠāļšāļāļēāļĢāļ“āđŒ:

5 āļ›āļĩāļ‚āļķāđ‰āļ™āđ„āļ›

āļ—āļąāļāļĐāļ°:

ETL, Compliance, Automation

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, build, and maintain scalable and secure data pipelines on cloud platforms (AWS/GCP/Azure). - Architect and implement data lake, data warehouse, and data mart solutions for enterprise workloads.
  • Develop and optimize ETL/ELT pipelines using modern tools and cloud-native services.
  • Work closely with Data Analysts, Data Scientists, and Business teams to support analytical and ML use cases.
14 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļ›āļ•āļ— āļŠāļģāļĢāļ§āļˆāđāļĨāļ°āļœāļĨāļīāļ•āļ›āļīāđ‚āļ•āļĢāđ€āļĨāļĩāļĒāļĄ āļˆāļģāļāļąāļ” āļĄāļŦāļēāļŠāļ™ 10
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļ›āļ•āļ— āļŠāļģāļĢāļ§āļˆāđāļĨāļ°āļœāļĨāļīāļ•āļ›āļīāđ‚āļ•āļĢāđ€āļĨāļĩāļĒāļĄ āļˆāļģāļāļąāļ” āļĄāļŦāļēāļŠāļ™ 10

āļ—āļąāļāļĐāļ°:

SQL, ETL, Project Management, 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‰

  • Consolidate requirements from various business functions and create common business data models within data warehouse for each business function to serve business needs.
  • Working with Data Governance, Data Management, and Data Engineering team to setup data warehouse model and working with business users to develop data marts.
  • Assessing the effectiveness and accuracy of data sources and data gathering techniques.
6 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
Upload ResumeUpload Resume
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™ Amaris Consulting Bangkok 11
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ Amaris Consulting Bangkok 11
āļāļĢāļļāļ‡āđ€āļ—āļž,

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‰

  • We are looking for a Data & AI Consultant (Mid-level) to support data-driven projects and AI initiatives.
  • In this role, you will be responsible for preparing, transforming, and structuring data to enable efficient analytics and machine learning use cases, while ensuring alignment with business requirements.
  • Your missions
1 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļ›āļ•āļ— āļŠāļģāļĢāļ§āļˆāđāļĨāļ°āļœāļĨāļīāļ•āļ›āļīāđ‚āļ•āļĢāđ€āļĨāļĩāļĒāļĄ āļˆāļģāļāļąāļ” āļĄāļŦāļēāļŠāļ™ 12
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļ›āļ•āļ— āļŠāļģāļĢāļ§āļˆāđāļĨāļ°āļœāļĨāļīāļ•āļ›āļīāđ‚āļ•āļĢāđ€āļĨāļĩāļĒāļĄ āļˆāļģāļāļąāļ” āļĄāļŦāļēāļŠāļ™ 12

āļ›āļĢāļ°āļŠāļšāļāļēāļĢāļ“āđŒ:

3 āļ›āļĩāļ‚āļķāđ‰āļ™āđ„āļ›

āļ—āļąāļāļĐāļ°:

Industry trends, SQL, NoSQL, 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‰

  • Design and work on all aspects of bringing ML models into production, develop CI/CD pipelines by collaborating with other disciplines such as data engineering, application development, cloud infrastructure, and security to implement AI solutions in production.
  • Work collaboratively with data scientists along the machine learning lifecycle from data pipeline, data preparation, model deployment, and model monitoring.
  • Understand and assess AI/ML industry trends to leverage technologies, continuously i ...
6 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āđ„āļ—āļĒāđ€āļšāļŸ 13
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āđ„āļ—āļĒāđ€āļšāļŸ 13
āļ„āļĨāļ­āļ‡āđ€āļ•āļĒ, āļāļĢāļļāļ‡āđ€āļ—āļž, āđ„āļ­āļ—āļĩ / āđ€āļ‚āļĩāļĒāļ™āđ‚āļ›āļĢāđāļāļĢāļĄ ,āļāļēāļĢāļˆāļąāļ”āļāļēāļĢ āđ„āļ­āļ—āļĩ / āđ€āļ‚āļĩāļĒāļ™āđ‚āļ›āļĢāđāļāļĢāļĄ,āļāļēāļĢāļˆāļąāļ”āļāļēāļĢ

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 Engineer Manager āļĄāļĩāļšāļ—āļšāļēāļ—āļŠāļģāļ„āļąāļāđƒāļ™āļāļēāļĢāļ­āļ­āļāđāļšāļš āļžāļąāļ’āļ™āļē āđāļĨāļ°āļšāļĢāļīāļŦāļēāļĢāļˆāļąāļ”āļāļēāļĢāđ‚āļ„āļĢāļ‡āļŠāļĢāđ‰āļēāļ‡āļžāļ·āđ‰āļ™āļāļēāļ™āļ”āđ‰āļēāļ™āļ‚āđ‰āļ­āļĄāļđāļĨ (Data Infrastructure) āļ‚āļ­āļ‡āļ­āļ‡āļ„āđŒāļāļĢ āđ€āļžāļ·āđˆāļ­āļĢāļ­āļ‡āļĢāļąāļšāļāļēāļĢāđƒāļŠāđ‰āļ‡āļēāļ™āļ”āđ‰āļēāļ™ Analytics, AI āđāļĨāļ° Business Intelligence āđ‚āļ”āļĒāļ—āļģāļŦāļ™āđ‰āļēāļ—āļĩāđˆāļ™āļģāļ—āļĩāļĄ Data Engineer āđāļĨāļ°āļ—āļģāļ‡āļēāļ™āļĢāđˆāļ§āļĄāļāļąāļšāļ—āļĩāļĄ Data, Product āđāļĨāļ° Business āđ€āļžāļ·āđˆāļ­āļŠāđˆāļ‡āļĄāļ­āļšāđ‚āļ‹āļĨāļđāļŠāļąāļ™āļ‚āđ‰āļ­āļĄāļđāļĨāļ—āļĩāđˆāļĄāļĩāļ„āļļāļ“āļ āļēāļž āļĄāļĩāđ€āļŠāļ–āļĩāļĒāļĢāļ āļēāļž āđāļĨāļ°āļŠāļēāļĄāļēāļĢāļ–āļ‚āļĒāļēāļĒāđ„āļ”āđ‰ (Scalable & Reliable).
  • Data Architecture & Engineering
  • āļ­āļ­āļāđāļšāļšāđāļĨāļ°āļžāļąāļ’āļ™āļē Data Architecture (Data Lake / Data Warehouse / Data Pipeline)
āļ§āļąāļ™āļ™āļĩāđ‰
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŠāđˆāļ‡āđāļˆāđ‰āļ‡āđ€āļ•āļ·āļ­āļ™āļ‡āļēāļ™āđƒāļŦāļĄāđˆāļĨāđˆāļēāļŠāļļāļ”āļŠāļģāļŦāļĢāļąāļšETL
  • 1