Senior Data Engineer (Python, AWS, PySpark)

Eclaro Business Solutions, Inc; Metro Manila; Remote; PHP 5,707,000 - 8,244,000; Full time

Job summary

ECLARO is a leading professional services firm hiring a Senior Data Engineer to design, build, and optimize scalable data pipelines in a cloud-native environment. You will own ingestion, transformation, validation, and delivery of diverse data types to power analytics and AI initiatives.

The role emphasizes end-to-end ETL/ELT, data modeling, governance, and API-driven data services. A remote setup is offered with night US-hours, requiring strong collaboration with cross-functional teams.

Qualifications

• Bachelor's degree or higher in a relevant field.
• Minimum 5+ years of professional data engineering experience with end-to-end ETL/ELT pipelines.

Responsibilities

• Build robust ETL/ELT workflows handling structured, semi-structured, and unstructured data at scale.
• Design data models and ontologies to maximize analytical value for downstream use cases.
• Implement data validation, cleansing, reconciliation, and integrity checks across ingestion processes.
• Develop APIs and data services exposing data to internal applications and platforms.
• Optimize queries and data workflows for performance, scalability, and resilience.
• Collaborate with analytics, AI, and platform teams to integrate new data sources.
• Maintain detailed documentation for pipelines, data models, metadata, lineage, and integration processes.
• Monitor ETL/ELT processes for efficiency and data quality, including alerting.

Skills

Python

PySpark

Airflow

Pandas

SQLAlchemy

ETL/ELT

Data Modeling

Data Governance

Education

Bachelor's degree or higher in Computer Science, Computer Engineering, Data Science, or related field

Tools

Airflow

SQL

NoSQL

Pandas

SQLAlchemy

PySpark

Job description

Senior Data Engineer (Python, AWS, PySpark)

ECLARO: A quick Summary

ECLARO is an award-winning professional services firm headquartered in New York City and operating in the U.S., Canada, UK, Ireland, Australia and the Philippines. We are dedicated to a singular purpose: providing the Right People to meet every client's needs and solve business challenges through strategic staffing, permanent placement, custom outsourcing & offshoring. Utilizing our proprietary TRINIT-E® Service Maturity Model, we help clients implement programs to promote innovation, automation and process improvement.

Role Title: Senior Data Engineer (Python, AWS, PySpark)

Set-up: Remote

Schedule: Night Shift (US Business Hours)

About the Role:

The Data Engineer, will design, build, and optimize scalable data pipelines and services that power analytics, AI/ML, and internal applications across the enterprise. This role owns the ingestion, transformation, validation, and delivery of structured, semi-structured, and unstructured data in a cloud-native environment.

The ideal candidate brings strong experience building robust ETL/ELT workflows, designing scalable data models, and exposing trusted data through APIs and reusable data services. This role will partner closely with analytics, application, platform, and AI teams to ensure data is high-quality, governed, performant, and ready for downstream use.

What You'll Do

• Build robust ETL/ELT workflows that handle structured, semi-structured, and unstructured data sources at scale.
• Design data models and ontologies that maximize analytical value and support graph-oriented and downstream application use cases.
• Implement data validation, cleansing, reconciliation, and integrity checks across ingestion processes to ensure consistent, trustworthy data.
• Develop APIs and data services that expose graph and enterprise data to internal applications and platforms.
• Optimize queries and data workflows for performance, scalability, and resilience.
• Collaborate with subject matter experts and technical stakeholders to identify, evaluate, and integrate new data sources.
• Maintain detailed documentation for pipelines, data models, metadata, lineage, and integration processes.
• Monitor and tune ETL/ELT processes for efficiency, resilience, and scalability, including alerting for data quality issues.

Qualifications

• Bachelor's degree or higher in Computer Science, Computer Engineering, Data Science, or a related field.
• 5+ years of professional experience in data engineering, including end-to-end ownership of ETL/ELT pipeline design, development, deployment, and monitoring.
• Practical experience implementing data validation, cleansing, transformation, and reconciliation processes to ensure high-quality, trustworthy datasets.
• Strong programming skills in Python and experience with common data engineering libraries and frameworks such as Pandas, SQLAlchemy, PySpark, and/or Airflow.
• Deep experience with relational (SQL) and NoSQL databases, data warehouse platforms, and schema/model design.
• Experience with data governance, metadata management, and lineage tracking.
• Experience with AI-embedded workflows.