Data Engineer (ETL, Python, SQL)

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Job Description

Summarized Purpose:

We are offering an opportunity for a Mid-Level Data Engineer to design build test tune and support production data pipelines using PySpark Python advanced SQL AWS data services secure data handling practices and AI-assisted data engineering capabilities.

Education/Experience:

• Bachelors degree or equivalent in Computer Science Information Technology Data Engineering or related field

• 3-5 years of experience in data engineering ETL development SQL AWS data platforms or production data pipeline support

Major Job Responsibilities:

• Develop test tune and maintain ETL and data pipelines using PySpark Python SQL and AWS services

• Support ingestion and transformation of flat files relational databases APIs data warehouses and enterprise data sources

• Collaborate with business analysts data architects QA DevOps and senior engineers to implement source-to-target mappings and data solutions

• Implement CDC incremental load design idempotent pipeline processing and data reconciliation patterns for reliable data movement

• Maintain technical documentation mapping specifications data catalog updates runbooks automated tests and release support materials

Knowledge Skills and Abilities:

• Hands-on experience with PySpark Python advanced SQL ETL best practices data modeling and large-scale data processing

• Deep knowledge of Redshift performance tuning including distribution keys sort keys compression encoding Spectrum materialized views WLM vacuum and analyze

• Strong knowledge of Athena optimization including partition pruning file formats compression schema evolution and cost-efficient query design

• Strong understanding of DynamoDB data modeling access-pattern-based design capacity planning GSIs/LSIs TTL Streams and performance tuning

• Exposure to secure PHI/PII handling including encryption access controls auditability retention masking and de-identification where applicable

• Strong analytical troubleshooting documentation communication and cross-functional collaboration skills

Must Have Skills:

• PySpark Python advanced SQL ETL development and data pipeline implementation experience

• AWS data services experience including S3 Glue Lambda Step Functions ECS DynamoDB Redshift PostgreSQL SQL Server and Athena integration

• Flat-file ingestion source-to-target mapping transformation logic CDC incremental loads idempotent processing reconciliation and data quality checks

• CI/CD GitHub workflows automated testing and release management for data pipelines and database changes

• Problem-solving production support debugging documentation and Agile delivery skills

Good to Have Skills:

• Exposure to AI-assisted mapping automation and use of LLMs for data cleaning data quality checks transformation logic or documentation

• Familiarity with RAG patterns embeddings vector databases semantic search or AI-enabled data discovery solutions

• Understanding of healthcare data standards such as HL7 FHIR CCD claims data EMR extracts clinical trial data and patient de-identification

• Familiarity with infrastructure as code such as Terraform or CloudFormation plus Databricks Snowflake streaming observability or DevOps practices

Working Hours:

• Philippines: 08:00 PM to 05:00 AM PHT

Required Experience:

IC

Employment Type : Full-Time
Experience: years
Vacancy: 1