Data Engineer (ETL, Python, SQL)

Thermo Fisher Scientific · Taguig City, Philippines

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Role summary

Thermo Fisher Scientific seeks a mid-level data engineer to design and maintain production ETL pipelines using PySpark, Python, SQL, and AWS services. The role involves supporting data ingestion, transformation, and collaboration across teams to deliver reliable data solutions.

What they're looking for

Bachelor's degree in Computer Science, Information Technology, Data Engineering, or related field
3-5 years of data engineering, ETL development, SQL, or AWS data platform experience
Proficiency in PySpark, Python, advanced SQL, and ETL best practices
Hands-on experience with AWS data services: S3, Glue, Lambda, Redshift, DynamoDB, Athena
Strong knowledge of Redshift and Athena performance tuning and optimization
Experience with CI/CD, GitHub workflows, automated testing, and release management

What you'll be doing

Develop, test, tune, and maintain ETL and data pipelines using PySpark, Python, SQL, and AWS
Support ingestion and transformation from flat files, databases, APIs, data warehouses, and enterprise sources
Implement CDC, incremental loads, idempotent processing, and data reconciliation patterns
Collaborate with business analysts, data architects, QA, DevOps, and senior engineers on data solutions
Maintain technical documentation, mapping specifications, data catalogs, runbooks, and automated tests

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Date posted14 days ago

Last source check1 day ago

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