Senior AWS Data Engineer — Cloud-Native Data Platform Lead

Sharesource

Davao City

On-site

PHP 1,339,200 - 2,678,400

Full time

14 days+

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Job summary

Sharesource is seeking a Senior AWS Data Engineer with 5+ years of experience to design, build, and support modern cloud-native data platforms on AWS. The role emphasizes AWS-native solutions, data governance, and scalable pipelines to power analytics and BI.

Remote role with local Philippines-based residency required for compliance and occasional onsite events. Strong focus on ingestion, transformation, storage, governance, and cost-optimised operations across data lakes and downstream

Qualifications

  • 5+ years delivering enterprise data engineering solutions.
  • Strong experience designing cloud-native data engineering solutions on AWS.
  • Experience designing and supporting modern data lake architectures.
  • Experience building scalable ETL/ELT pipelines.
  • Experience working with structured, semi-structured, and unstructured data.

Responsibilities

  • Design, build, and support modern cloud-native data engineering platforms on AWS.
  • Develop and maintain scalable ETL/ELT pipelines for data ingestion, transformation, and processing.
  • Architect and manage data lake solutions to support multiple data formats.
  • Integrate data from APIs, SaaS platforms, databases, streaming platforms, and file-based sources.
  • Apply cloud-native design principles using AWS-managed services.
  • Ensure data platforms are reliable, scalable, and cost-efficient.

Skills

AWS data engineering
Python
SQL
ETL/ELT design
Data lake design

Tools

Terraform
GitHub
CI/CD
Airflow
Spark

Job description

Sharesource is seeking a Senior AWS Data Engineer with 5+ years of experience to design, build, and support modern cloud-native data platforms on AWS. The role emphasizes AWS-native solutions, data governance, and scalable pipelines to power analytics and BI.

Remote role with local Philippines-based residency required for compliance and occasional onsite events. Strong focus on ingestion, transformation, storage, governance, and cost-optimised operations across data lakes and downstream

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