Senior Data Engineer (Python)

About Jobgether

Jobgether is a pioneering HR Tech startup, operating entirely remotely, and leading the revolution in the world of work. As the largest job search engine designed exclusively for remote workers, we believe that flexibility is the cornerstone of the future of work. Our mission is to empower individuals to discover opportunities that align seamlessly with their unique lifestyles.

On the Jobgether platform, companies can showcase their commitment to flexibility and remote work policies, attracting top-tier talent from across the globe. Our diverse team of 30 individuals is located in Spain, Belgium, Israel, France, Colombia, Madagascar, Italy, Ukraine, Portugal, the USA, and India, embodying the true spirit of remote work.

We operate on the fundamental principle that work should be conducted on your terms—how you want, when you want, and from wherever you want. We place a premium on accountability, valuing outcomes above all else. At Jobgether, it's not about where you work; it's about what you achieve.

What will you do?

Join our dynamic Content and Data team as a Senior Data Engineer, where you'll play a pivotal role in developing and scaling our matching algorithm using AI together with our Data Engineering Team. Jobgether's platform, which aggregates over 10,000 new job listings daily and identifies emerging remote companies.

We are looking for an experienced Senior Data Architect and Engineer with a strong command of both relational and non-relational database architectures. The ideal candidate will be responsible for designing, implementing, and maintaining robust data architecture solutions, as well as managing and optimizing existing data flows. This role requires deep technical expertise in data infrastructure, a strategic mindset to propose alternative data flow solutions, and hands-on capabilities to operate and support diverse data processes, including scrapers, machine learning (ML) workflows, and data pipelines.

Key Responsibilities

• Data Architecture Design: Develop scalable and efficient data architectures for both relational (e.g., MySQL, PostgreSQL) and non-relational (e.g., MongoDB, NoSQL) databases, ensuring compatibility and optimization across systems.

• Solution Implementation: Lead the implementation of data architecture solutions, focusing on performance, scalability, and reliability.

• Data Flow Optimization: Analyze current data flows, identifying opportunities to improve or redesign for enhanced efficiency, accuracy, and flexibility.

• End-to-End Data Pipeline Management: Build, operate, and maintain data pipelines, ensuring seamless integration of data from various sources and providing high-quality data to downstream processes.

• Support & Operations: Provide operational support for developed data flows, maintaining scrapers, data pipelines, and ML workflows, ensuring they perform optimally in production environments.

• Collaboration & Documentation: Work closely with cross-functional teams to understand data needs, document architectural designs, and maintain thorough documentation of data workflows and processes.

What You Bring to the Role

Mandatory Qualifications

• Educational Background: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.

• Experience: Minimum of 5 years of experience in data engineering, with a strong focus on building and managing data pipelines and infrastructure.

• Programming Proficiency: 5 years of experience with Python 

• Data Modeling: Strong understanding of data modeling, schema design, and data warehousing concepts.

• Database Knowledge: Proficiency with relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases - Experience with MongoDB.

• Cloud Platforms: Experience with AWS.

• Big Data Technologies: Hands-on experience with big data frameworks and tools like Hadoop, Spark, or Kafka.

• Problem-Solving Skills: Excellent analytical and troubleshooting abilities.

• Language Skills: Fluency in English and Spanish.

Preferred Qualifications

• Machine Learning Deployment: Experience deploying machine learning models into production environments.

• DevOps Practices: Familiarity with CI/CD pipelines, containerization (Docker), and orchestration tools (Kubernetes).

• Data Security: Knowledge of data privacy regulations and security best practices.

• Communication Skills: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.

Why Join Us

• Remote Work Culture: Embrace the freedom to work from anywhere in the world.

• Innovative Environment: Be part of a forward-thinking team that's shaping the future of remote work.

• Professional Growth: Opportunity to work on cutting-edge technologies and challenging projects that drive real impact.

• Diverse Team: Collaborate with a global team of passionate professionals.