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Data Engineer - Mid level (Snowflake)

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Summary

Mid-level data engineer in Bonifacio Global City who designs and maintains ETL pipelines, data marts, and an in-house Snowflake data warehouse on AWS (Glue, RDS, Fargate), programs in Java/Python, and supports BI and analytics (Qlik), including migrating legacy databases into the warehouse.

  • Data Pipeline Engineering & ETL Development (AWS Glue, ETL concepts)

  • Data Warehousing & Data Modeling (Snowflake, Data Marts, Data Migration)

  • Programming & Scripting (Java, Python)

  • Cloud Data Technologies (AWS RDS, AWS Fargate, AWS Ecosystem) Database Systems (Snowflake, PostgreSQL, MS SQL)

  • Business Intelligence & Analytics Support (BI Datasets, Qlik, Advanced Analytics)
    Data Quality, Maintenance & Reliability

  • Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related quantitative discipline from a top-tier university

  • Certified in AWS Data Engineer Specialty or AWS Solutions Architect Associate

  • Snowflake SnowPro Core Certification

  • 7+ years of experience in data engineering or a similar role, preferably in the financial industry

  • Strong understanding or hands-on experience with Enterprise Agile frameworks (e.g., Kanban, SAFe, SCRUM)

  • Solid understanding of ETL, data warehousing, BI (e.g., Qlik), and advanced data analytics concepts

  • Deep knowledge of cloud-enabled technologies such as AWS RDS, AWS Fargate, etc.

  • Experience with databases and data warehouses including Snowflake, PostgreSQL, and MS SQL

  • Strong programming skills with advanced knowledge of Java and/or Python

  • Practical experience with ETL tools such as AWS Glue

  • Excellent critical thinking, analytical, and problem-solving skills

  • Strong communication skills with a team-oriented mindset

Responsibilities:

Design

● Analyze internally and externally sourced raw data to generate BI and advanced analytics datasets based on stakeholder requirements

● Design data pipelines to curate sourced data into the in-house data warehouse

● Develop data marts to facilitate dataset consumption from the in-house data warehouse by business and IT stakeholders

● Design data model changes in alignment with in-house data warehouse standards

● Define and plan migration execution activities to transition data from existing database solutions to the in-house data warehouse

Engineer

● Perform regular housekeeping of raw data and data stored in the in-house data warehouse

● Build and maintain data pipelines and data platforms

● Develop data solution prototypes to support evolving business needs

● Explore methods to enhance data quality and reliability

● Identify and pursue opportunities to acquire higher-quality raw data

● Develop analytical tools to support BI and advanced analytics activities Execute data migration from existing databases to the in-house data warehouse

● Promote and champion data engineering standards and best-in-class methodologies

Skills

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See also

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