Senior Data Engineer

iScale Solutions; Metro Manila; A distancia; PHP 900.000 - 1.500.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive Salary

Vacation & Sick Leave credits

Health Coverage

Government Benefits

Learning Opportunities

Team Engagement

Modern Tools

Career Growth

Inclusive Culture

Descripción de la vacante

iScale Solutions is seeking a Senior Data Engineer to own end-to-end data pipelines, optimize processing, and lead a small engineering team in a remote capacity. You will design scalable ETL/ELT solutions, implement Airflow-based workflows, and collaborate with analytics and product teams.

Required expertise includes SQL, Hive, Python, Spark, and AWS services (S3, Athena, EC2, EMR). Experience with data governance, AI-assisted automation, and Jira/Confluence is highly valued.

Formación

• 5+ years of professional experience in data engineering, with ownership of production data pipelines.
• Strong SQL expertise including complex joins, window functions, transformations and troubleshooting.
• Proficiency in Hive and Hadoop ecosystem, including partitioning and distributed processing concepts.
• Proficiency in Python for data processing, automation, and production code.
• Hands-on experience with Amazon S3, Athena, EC2, and EMR.
• Experience with Apache Airflow or similar ETL/workflow orchestration tools.
• Ability to translate business requirements into technical designs with minimal supervision.
• Strong documentation and communication skills for cross-functional stakeholders.
• Experience with Jira and Confluence for task tracking and documentation.
• Exposure to AI capabilities and basic AI-assisted automation.

Responsabilidades

• Own data pipeline development: design, develop, and maintain ETL/ELT pipelines for large-scale datasets across sources.
• Define processing logic, data models, integration approaches, and workflow dependencies; focus on scalability and cost.
• Write SQL, Hive, and Python; apply Spark where appropriate to optimize processing.
• Build and manage AWS workflows using S3, Athena, EC2, and EMR; monitor resources.
• Develop automated workflows with Airflow, including scheduling, retries, and alerting.
• Monitor pipeline performance and data freshness; investigate failures and perform root cause analysis.
• Maintain data quality and governance with validation checks and data dictionaries.
• Lead and mentor 2–3 engineers; review designs and track delivery commitments.
• Collaborate with analytics, product, engineering, and data science teams to align requirements and priorities.
• Maintain solution designs, data flow diagrams, data dictionaries, and runbooks; document in Confluence.
• Apply AI to engineering workflows; build simple AI agents and validate outputs.
• Support agile delivery via Jira; participate in sprint planning and technical reviews.

Conocimientos

SQL

Hive

Python

Airflow

AWS

Spark

OpenAI Codex

Snowflake

Jira

Confluence

Herramientas

PySpark

Scala

Snowflake

OpenAI Codex

Git

Descripción del empleo

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.