Senior Data Engineer

iScale Solutions; Philippines; Remote; PHP 1,200,000 - 2,400,000; Full time

Benefits offered by this job

Competitive salary package

Vacation and sick leave credits

Health coverage

SSS, PhilHealth, Pag-IBIG

Job summary

iScale Solutions is seeking a senior data engineer for a fully remote role based in the Philippines. You will own end-to-end data pipelines, design scalable data models, and implement reliable ETL/ELT processes across platforms.

The role emphasizes Python, SQL, Hive, Spark, AWS (S3, Athena, EMR), and Airflow. You will mentor a small team of 2–3 engineers, collaborate with analytics, product, and data science teams, and ensure data quality, governance, and production reliability.

Qualifications

• 5+ years of professional experience in data engineering and production pipelines.
• Strong SQL skills with complex joins, windows, and performance tuning.
• Hive and Hadoop ecosystem knowledge for large-scale processing.
• Python for data processing and automation; Spark when needed.
• Hands-on AWS (S3, Athena, EC2, EMR) experience.
• Experience with Airflow or similar ETL/workflow tools.

Responsibilities

• Own data pipeline development: design, build, maintain ETL/ELT pipelines.
• Lead technical design and data models for scalable processing.
• Develop and optimize data processing using SQL, Hive, Python, Spark.
• Build and manage AWS workflows with S3, Athena, EC2, EMR.
• Manage workflow orchestration and monitoring with Airflow.
• Ensure production reliability, data quality, and governance.
• Lead and mentor a 2–3 engineer team and review work.
• Collaborate with analytics, product, engineering, and data science.
• Maintain solution docs, data flow diagrams, and runbooks.
• Explore AI opportunities to improve workflows and automation.

Skills

Data pipelines

SQL

Hive

Python

AWS

Airflow

Spark

OpenAI Codex

Jira

Confluence

Tools

Airflow

Snowflake

OpenAI Codex

Snowflake Cortex

Job description

This is a remote position.

Responsibilities

• Own data pipeline development: Design, develop, and maintain reliable ETL/ELT pipelines for ingesting, transforming, and delivering large-scale datasets across multiple platforms and sources.
• Lead technical design: Define processing logic, data models, integration approaches, and workflow dependencies, considering scalability, maintainability, security, and cost.
• Develop and optimize data processing: Write efficient SQL, Hive queries, and Python code. Apply distributed processing frameworks such as Spark where appropriate.
• Build and manage AWS workflows: Develop and support data solutions using Amazon S3, Athena, EC2, and EMR, including monitoring and resource optimization.
• Manage workflow orchestration: Build and maintain automated workflows using Apache Airflow or comparable orchestration tools, including scheduling, dependencies, retries, alerting, and recovery.
• Ensure production reliability: Monitor pipeline performance and data freshness, investigate failures, perform root cause analysis, and implement improvements that prevent recurring issues.
• Maintain data quality and governance: Establish validation checks, reconciliation processes, lineage documentation, and appropriate access controls throughout the data lifecycle.
• Lead and mentor a small team: Guide 2-3 engineers, break requirements into actionable tasks, review code and designs, support troubleshooting, and track delivery commitments.
• Collaborate with stakeholders: Work closely with analytics, product, engineering, and data science teams to clarify requirements, agree on priorities, communicate progress, and manage dependencies.
• Maintain technical documentation: Create and update solution designs, data flow diagrams, data dictionaries, operating procedures, and support runbooks using Confluence or similar platforms.
• Apply AI to engineering workflows: Identify practical opportunities to use AI for development, documentation, troubleshooting, and automation. Build simple AI agents and validate their outputs before operational use.
• Support agile delivery: Manage work through Jira, contribute to sprint planning and technical reviews, and coordinate across regions and work schedules as required.

Requirements

• 5+ years of professional experience in data engineering, with demonstrated ownership of production data pipelines and large-scale data processing.
• Strong SQL expertise, including complex joins, window functions, transformations, query tuning, and troubleshooting.
• Strong working knowledge of Hive and the Hadoop ecosystem, including partitioning, storage formats, and distributed data processing concepts.
• Proficiency in Python for data processing, automation, integration, and maintainable production code.
• Hands-on experience with Amazon S3, Athena, EC2, and EMR.
• Strong experience with Apache Airflow or another ETL/workflow orchestration tool, with Airflow preferred.
• Experience implementing data quality checks, monitoring, error handling, and operational support processes.
• Ability to translate business requirements into technical designs and deliver solutions with minimal supervision.
• Strong documentation and communication skills, including the ability to explain technical issues clearly to business and technical stakeholders.
• Working experience with Jira and Confluence for task tracking, delivery coordination, and documentation.
• Practical understanding of AI capabilities and limitations, along with hands-on experience creating simple AI agents or AI-assisted automations.
• Experience with version control, code reviews, and collaborative development practices.

Preferred Qualifications

• Hands-on experience with Apache Spark using PySpark or Scala.
• Experience with Snowflake, including data transformation, query optimization, and integration with cloud data pipelines.
• Practical experience using OpenAI Codex for engineering tasks and Snowflake Cortex for AI-enabled data workflows.
• Previous experience mentoring engineers, leading technical delivery, or managing a small team. Formal people management experience is an added advantage.
• Experience supporting marketing technology, audience data, campaign reporting, or customer analytics.

Benefits

• Competitive Salary Package: Receive a pay package that matches your skills and experience.
• Vacation and Sick Leave credits: Enjoy vacation and sick leave credits to maintain work-life balance.
• Health Coverage: Get medical, dental, and vision insurance for you and your dependents.
• Government-Mandated Benefits: Full coverage of all statutory benefits like SSS, PhilHealth, and Pag-IBIG.
• Learning Opportunities: Access training, certifications, and mentorship to grow your career.
• Team Engagement: Join team-building activities and wellness programs.
• Modern Tools: Use the latest technology to excel in your role.
• Career Growth: Clear paths for promotion and professional development.
• Inclusive Culture: Be part of a diverse, supportive, and collaborative global team.