Senior Data Engineer

ECLARO; Quezon City; On-site; PHP 900,000 - 1,500,000; Full time

Job summary

ECLARO is seeking a Data Engineer to design, build, and optimize scalable data pipelines and services powering analytics, AI/ML, and internal applications. The role centers on ingestion, transformation, validation, and delivery of diverse data in a cloud-native environment.

You will own end-to-end ETL/ELT workflows, design robust data models, expose data via APIs and data services, and partner with analytics, platform, and AI teams to ensure high quality, governance, and performance.

Qualifications

• End-to-end ownership of ETL/ELT pipeline design, development, deployment, and monitoring.
• Design scalable data models and governance strategies for trusted data.
• Build robust data ingestion, validation, cleansing, and quality checks.
• Develop APIs and data services exposing graph and enterprise data for internal apps.
• Collaborate with analytics, platform, and AI teams to ensure data readiness and performance.

Responsibilities

• Build robust ETL/ELT workflows that handle structured, semi-structured, and unstructured data at scale.
• Design data models and ontologies to maximize analytical value.
• Implement data validation, cleansing, reconciliation, and integrity checks.
• Develop APIs and data services for internal applications and platforms.
• Optimize queries and data workflows for performance and scalability.
• Collaborate with subject matter experts to integrate new data sources.
• Maintain documentation for pipelines, data models, lineage, and integration processes.
• Monitor ETL/ELT processes for efficiency and data quality.

Skills

Python

ETL/ELT Design

Pandas

SQLAlchemy

PySpark

Airflow

APIs

Data Governance

Education

Bachelor’s degree or higher in CS/CE/DS

Tools

Relational databases

NoSQL databases

Data warehouses

API development

Job description

Data Engineer

Role Title: Data Engineer

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.

Position Summary

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.