Senior Data Engineer

Posted Yesterday
Be an Early Applicant
Hiring Remotely in Makati City, PHL
In-Office or Remote
Senior level
Information Technology • Marketing Tech • Professional Services • Design
The Role
Own the design, development, optimization, and reliability of large-scale data pipelines across AWS and Hadoop environments. Lead technical design, workflow orchestration, data quality, governance, monitoring, documentation, and production support. Mentor a small engineering team, collaborate with cross-functional stakeholders, and apply AI-assisted automation. Required expertise includes SQL, Python, Hive, AWS services, Airflow, and data engineering operations, with Spark and Snowflake experience preferred.
Summary Generated by Built In

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

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

What we offer:


  • 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.



Skills Required

  • 5+ years of professional experience in data engineering, including 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 production code.
  • Hands-on experience with Amazon S3, Athena, EC2, and EMR.
  • Strong experience with Apache Airflow or another ETL/workflow orchestration tool; 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 for explaining technical issues 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, with hands-on experience creating simple AI agents or AI-assisted automations.
  • Experience with version control, code reviews, and collaborative development practices.
  • 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.
  • Experience supporting marketing technology, audience data, campaign reporting, or customer analytics.
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The Company
HQ: Makati City
600 Employees
Year Founded: 2012

What We Do

iScale Solutions is a full-service outsourcing company providing staff augmentation, IT services, business process outsourcing, digital marketing, creative solutions, and managed IT support.

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