.Gain full access to exclusive job listings from leading companies worldwide.Verified, High-Quality Jobs OnlyNo ads, scams, or junk-just genuine opportunities.Explore thousands of open positions tailored to your lifestyle, including flexible remote jobs.Exclusive Resume ReviewReceive expert feedback with personalized suggestions to enhance your resume.About PayJoyPayJoy is a mission-first financial service provider dedicated to helping under-served customers in emerging markets to achieve financial stability and success.
We lend through our patented technology that turns a smartphone into digital collateral, and our cutting-edge machine learning, data science, and anti-fraud AI allow us to offer the lowest cost and qualify the most customers in the industry.
As of 2024, we have brought billions of dollars in credit to 12 million customers, doubling in the last two years while remaining strongly profitable and sustainable for the long term.This RoleAs a Senior Data Engineer, you will play a key role in designing, developing, and maintaining scalable and efficient data pipelines to support the organization's data needs.
You will be responsible for ensuring the smooth and reliable flow of data across various systems and platforms, enabling teams to access accurate and actionable data for decision-making.
Your expertise will be crucial in optimizing data architecture, transforming raw data into usable formats, and ensuring data integrity, security, and availability.A successful Senior Data Engineer will possess strong technical expertise in programming languages like Python, alongside experience with big data technologies such as Spark and Kafka, and cloud platforms like AWS or GCP.
They will demonstrate problem-solving skills, focusing on data quality, governance, and scalable architecture, ensuring reliable, high-performance data pipelines.
Excellent collaboration and communication skills are essential, enabling them to work effectively with cross-functional teams while translating technical complexities for non-technical stakeholders.
With a mindset of continuous learning, they will stay updated on emerging tools and best practices, and provide leadership or mentorship to junior team members.ResponsibilitiesDesign and Develop Data Pipelines: Build, optimize, and maintain reliable, scalable, and efficient data pipelines for both batch and real-time data processing.Data Strategy: Develop and maintain a data strategy aligned with business objectives, ensuring data infrastructure supports current and future needs.Tool & Technology Selection: Evaluate and implement the latest data engineering tools and technologies that will best serve our needs, balancing innovation with practicality.Performance Tuning: Regularly review, refine, and optimize SQL queries across different systems to maintain peak performance.Identify and address bottlenecks, query performance issues, and resource utilization