Senior Data Engineer
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Summary
Senior Data Engineer in Taguig who designs, builds, and optimizes automated data pipelines, ETL/ELT workflows, and data models on cloud platforms, and supports large-scale data migrations. Core stack is Python, SQL, Databricks/Snowflake, and Microsoft Azure services like Data Factory and Synapse, working closely with business, analytics, and product teams.
About the role
Design, build, and optimize automated data pipelines, ETL/ELT processes, and data models to ingest, process, and store large volumes of data within cloud-based platforms. Partner with business, analytics, and product teams to translate data requirements into effective technical solutions that support strategic initiatives.
Qualifications
- 8 years or above of total Data Engineering experience, with strong exposure to large-scale data pipelines, ETL/ELT development, and enterprise or cloud-based data platforms
- Proven experience designing, building, and optimizing scalable data solutions in modern data environments
- Python – At least 4 out of 5 proficiency level, with strong hands‑on experience in data transformation, automation, and pipeline development
- SQL – At least 3 out of 5 proficiency level, with demonstrated capability in complex queries, data modeling, and performance tuning
- Experience working with modern data cloud platforms, such as Databricks and/or Snowflake
- Experience with cloud services, preferably Microsoft Azure (e.g., Azure Data Factory, Azure Synapse, Azure Storage, etc.)
- Strong verbal and written communication skills
- Demonstrated leadership and technical influence
- Strong analytical, critical thinking, and problem-solving abilities
- Stakeholder and cross‑functional collaboration skills
Key responsibilities
- Design, build, and optimize automated data pipelines, ETL/ELT processes, and data models to ingest, process, and store large volumes of data within cloud-based platforms
- Support large‑scale data migration initiatives, ensuring data accuracy, performance efficiency, and minimal business disruption
- Develop and maintain ETL/ELT workflows to ingest, transform, and load data from multiple internal and external sources with a focus on scalability and reliability
- Partner with business, analytics, and product teams to translate data requirements into effective technical solutions that support strategic initiatives
- Design and deliver data marts and customized data extractions aligned with business and reporting needs
- Ensure compliance with enterprise data governance, security, and regulatory standards
- Monitor data pipeline health and performance, troubleshoot data incidents, and implement preventive and corrective measures
- Document data workflows, schemas, technical specifications, and operational runbooks to support operational stability and knowledge transfer
- Collaborate closely with product owners, data architects, and data scientists to maintain a reliable and efficient data infrastructure
- Drive continuous improvement of data engineering practices, tools, and automation frameworks