Sr Snowflake Data Engineer_Hybrid_BGC Taguig_Up to 200k

weSource Management Consultancy Firm; Taguig; Hybrid; PHP 2,031,120 - 2,432,880; Full time

Job summary

A management consultancy firm is urgently hiring a Senior Snowflake Data Engineer in Taguig. This hybrid role requires at least 7 years of experience in data engineering, preferably in the financial industry, and expertise in ETL processes, data warehouses, and AWS technologies. The successful candidate will lead the design and maintenance of data pipelines and collaborate with data teams. This position offers an attractive salary up to 200K PHP, with work scheduled for day shifts, Monday to Friday.

Qualifications

• At least 7+ years of experience in data engineering or relevant working experience.
• Experience working on Snowflake projects for 5+ years.
• Certified in AWS Data Engineer Specialty or AWS Solution Architect Associate.

Responsibilities

• Lead the design and build of in-house data platforms.
• Collaborate with data analysts and data scientists.
• Design data pipelines to curate sourced data into the in-house data warehouse.

Skills

ETL knowledge

Data warehouse and BI

Programming in Java and/or Python

Experience with AWS technologies

Strong analytical skills

Excellent communication

Education

Bachelor's or master's degree in Computer Science, IT, or related

Tools

AWS RDS

Snowflake

PostgreSQL

MS SQL

AWS Glue

Job description

Sr Snowflake Data Engineer_Hybrid_BGC Taguig_Up to 200k

Job Openings Sr Snowflake Data Engineer_Hybrid_BGC Taguig_Up to 200k

About the job Sr Snowflake Data Engineer_Hybrid_BGC Taguig_Up to 200k

We are urgently hiring for a Senior Snowflake Data Engineer

This is a hybrid work set-up, with 3 times onsite per week in BGC Taguig

Work schedule is Day Shift, Monday to Friday

Salary is up to 200K based on experience

At least 7+ years of experience in data engineering or relevant working experience in a similar role, preferably in the financial industry

Preferred Qualifications:

• Strong understanding or practical experience of at least one common Enterprise Agile Framework e.g., Kanban, SAFe, SCRUM, etc.
• Strong understanding of ETL, data warehouse and BI(Qlik) and Advanced Data Analytics concepts
• Deep knowledge of cloud-enabled technologies AWS RDS and AWS Fargate, etc.
• Experience with databases and data warehouses - Snowflake, PostgreSQL, MS SQL
• Strong programming skills with advanced knowledge of Java and/or Python
• Practical experience with ETL tools such as AWS Glue, etc.

Required Qualifications:

• Bachelors or masters degree in Computer Science, Information Technology, Engineering or related quantitative discipline from a top tier university.
• Certified in AWS Data Engineer Specialty or AWS Solution Architect Associate
• Snowflake SnowPro Core Certification mandatory and 5+ years of hands on experience working on snowflake projects.
• 7+ years of experience in data engineering or relevant working experience in a similar role, preferably in the financial industry
• Strong understanding or practical experience of at least one common Enterprise Agile Framework e.g. Kanban, SAFe, SCRUM, etc.
• Strong understanding of ETL, data warehouse and BI(Qlik) and Advanced Data Analytics concepts
• Deep knowledge of cloud-enabled technologies AWS RDS and AWS Fargate, etc. Experience with databases and data warehouses - Snowflake, PostgreSQL, MS SQL
• Strong programming skills with advanced knowledge of Java and/or Python
• Practical experience with ETL tools such as AWS Glue, etc.
• Strong critical-thinking, analytical and problem-solving skills
• Excellent communicator with team-oriented approach

About the Role:

A Senior Data Engineer is mid-level professional leading the design, build and evolution of the inhouse data platforms. You lead the construction of datasets requested by various stakeholders, the build and maintenance of the resulting data pipelines. You closely work in collaboration with our data analysts, data scientist and business application development teams in delivering data solutions.

Design

1. Analyse relevant internally and externally sourced data (raw data) to generate BI and Advanced Analytics datasets based on your stakeholders requirements
2. Design data pipelines to curate sourced data into the inhouse data warehouse
3. Design data marts to facilitate dataset consumption out of the inhouse data warehouse by business and IT internal stakeholders
4. Design data model changes that align with the inhouse data warehouse standards
5. Define migration execution activities to move data from existing database solutions to the inhouse datawarehouse
6. Regular housekeeping of raw data and data stored in the inhouse data warehouse
7. Build and maintenance of data pipelines and data platforms
8. Build data solution prototypes
9. Explore ways to enhance data quality and reliability
10. Identify and realize opportunities to acquire better data (raw data)
11. Develop analytical tooling to better support BI and Advanced Data Analytics activities
12. Execute data migration from existing databases to the inhouse data warehouse
13. Promote and champion data engineering standards and best-in-class methodology