Data Engineer (Hybrid Set-up)

Sprout Solutions Phil.

Mandaluyong

Hybrid

PHP 900,000 - 1,500,000

Full time

14 days+
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Job summary

Sprout Solutions Phil. is seeking a Data Engineer for a hybrid setup in Metro Manila. The role focuses on transforming data for analysis, designing and developing Sprout's data system, and supporting machine learning initiatives.

The engineer will ensure robust data delivery across projects and collaborate with software engineers, data scientists, and architects. You will build and optimize data models, pipelines and APIs, work with diverse data sources, and help deploy models created by the

Qualifications

  • Strong SQL/NoSQL knowledge and data engineering best practices.
  • Experience with SQL-based and NoSQL data stores.
  • Experience with data modeling (data warehouse/lake) and storage schemes.
  • Familiarity with ETL tools and processing frameworks (Spark/Hadoop).
  • Experience building and optimizing data pipelines and architectures.
  • Proficiency with Azure data services.
  • Familiarity with PowerBI or similar visualization tools.
  • Comfort with agile development and collaborating across teams.

Responsibilities

  • Build, optimize and maintain database models (conceptual/logical/physical).
  • Develop database solutions to store and retrieve information.
  • Assemble datasets meeting business requirements.
  • Build infrastructure for ETL from diverse data sources.
  • Monitor data integrity and adopt appropriate tools.
  • Improve system performance and scalability.
  • Redesign data architecture to support product and data initiatives.
  • Design, develop, test and deploy web service APIs.
  • Collaborate with Data Scientists to identify future needs.
  • Deploy models and algorithms developed by the Data Science team.

Skills

SQL & NoSQL
Python/Java/Scala
Data modeling
ETL pipelines
PowerBI
Azure
Analytical thinking
Problem solving
Team collaboration

Tools

Azure

Job description

About the job Data Engineer (Hybrid Set-up)

Data Engineers are mainly tasked with transforming data into a format that can be easily analyzed. The Data Engineer will be responsible for designing and developing Sprouts data system, processing and extracting data features and deploying the data science teams machine learning models. The Data Engineer will support our software engineers, architects and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.


Responsibilities:


  • Build, optimize and maintain conceptual, logical and physical database models

  • Develop database solutions to store and retrieve information

  • Assemble datasets that meet functional/non-functional business requirements

  • Build the infrastructure for optimal ETL from a wide variety of data sources

  • Monitor data integrity and adopt appropriate tools

  • Improve system performance

  • Optimize or re-design data architecture to support Sprouts next generation of products and data initiatives

  • Design, develop, test and deploy web service APIs

  • Work with Data Scientists to identify future needs and requirements

  • Deploy models and algorithms developed by the Data Science team


Requirements:


  • Extensive knowledge on databases (SQL and/or NoSQL) and data engineering best practices

  • Expertise in SQL and other programming languages(e.g. Python, Java, Scala, shell scripting etc.)

  • Experience with data modeling (data warehouse, data lake) and designing data storage schemes

  • Familiarity with data engineering and ETL software tools, hadoop, spark, talend, SSAS, etc. is also helpful

  • Experience building and optimizing data pipelines, architecture and datasets

  • Experience with Azure

  • A successful history of manipulating, processing and extracting value from large disconnected datasets

  • Familiarity with data visualization tools (e.g. PowerBI)

  • Familiarity with agile development as a project management methodology is a plus

  • Strong problem-solving and analytical skills

  • Must be self-motivated and comfortable supporting the data needs of multiple teams, systems and products

  • A good team player and willingness to learn

  • Strong innate desire and proven track record of continuous self-improvement (in learning, job expansion, extracurricular activities, etc.)

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