Senior Data Engineer_Hybrid_Shifting_BGC_Up to 170K

We are hiring for a Senior Data Engineer for a client based in BGC. This is a Hybrid work following a Shifting schedule. Salary is up to ₱170,000.00 based on experience. Key Requirements: 7+ years of experience in data engineering or a similar role, preferably in the financial industry Bachelors or Masters 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 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