Senior Data Engineer

Role Overview

• Responsible for creating and maintaining the knowledge materials for the scope of the team, regarding delivery on MSP customers.
• Act as a trusted advisor to customers, developing a deep understanding of their technical challenges and leveraging GCP technologies, patterns and practices to address them effectively.
• Work closely with the delivery teams, Google, and customer engineering teams to understand and use repeatable and consistent technology stacks across our customer projects.
• Help document and implement managed service processes that are aligned with a project's technology stack, and customer requirements.
• Follow & improve if applicable the best practices, processes and procedures relevant to the team’s activity.
• Ability and willingness to upskill and mentor colleagues, in order to ensure a smooth delivery across teams.
• Possibility to represent Qodea in the relationship with Google or customers. Availability for potential customer visits based on the needs.
• Handle customer escalations and facilitate any patches or fixes as needed to resolve any issues relating to their data platform.
• Investigate issues in and maintain data models to support analytics and reporting.
• Monitor and maintain data infrastructure to ensure availability, correctness and performance.
• Perform regular checks to ensure data pipelines and ML models are working correctly.
• Collaborate with the customer on a quarterly basis to ensure all requirements continue to be met.
• Scope and plan implementation of any customer changes/requirements.
• Maintain automated data pipelines to support data ingestion, ETL, and storage.

Requirements

• Experience with Google Cloud Platform (GCP) or other major cloud providers.
• Strong experience in Python with demonstrable experience in developing and maintaining data pipelines and automating data workflows.
• Proficiency in SQL, particularly BigQuery SQL for querying and manipulating large datasets.
• Experience with version control systems (e.g., Git).
• Strong expertise in Python, with a particular focus on libraries and tools commonly used in data engineering, such as Pandas, NumPy, Apache Airflow.
• Experience with data pipelines, ELT/ETL processes, and data wrangling.
• Dashboard analytics (PowerBI, Looker [Studio] or Tableau) experience.
• Worked in a client facing role previously and ability to communicate and translate business requirements into technical specifications.
• Collaborative, proactive, logical, methodical, and attentive to detail.
• Willingness to mentor and coordinate more junior members of the team.
• A can do attitude and team player.
• Excellent English, written and verbal.

Tech Stack

• Airflow
• Apache
• BigQuery
• Cloud
• ETL
• Google Cloud Platform
• Numpy
• Pandas
• Python
• SQL
• Tableau

Benefits

• Competitive base salary.
• De Minimis Allowance.
• 13th Month Pay: Equivalent to one month’s base salary, paid every December.
• Medical Insurance: HMO coverage for the employee plus up to two dependents (employer-paid).
• Sick Leave: 15 paid days per year, pro-rated from the start date.
• Annual Leave: 28 days per calendar year (January 1 – December 31), pro-rated based on start date.
• Birthday Leave: An extra paid day off for your birthday.
• Learning Leaves: Ten paid learning days per year.
• Philippine Public Holidays: Statutory holidays are included.
• Bereavement Leave: 3 paid days.
• Parental Leave: Maternity or Paternity leave.
• Flexible Work Arrangement: Hybrid model (two to three days in the office).
• Peer Recognition: 100 Bonusly points per month for peer recognition.
• Diversity and Inclusion