Data Analyst For Marketing Yr (Remote)

Data Analyst For Marketing Yr | Jobgether | Argentina

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.

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.

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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.

Key Responsibilities

• Data Infrastructure Development: Design, build, and maintain scalable data pipelines and ETL processes to collect, process, and store large volumes of structured and unstructured data.
• Data Scraping and Extraction: Develop and optimize data scraping and extraction solutions to gather job data from multiple sources efficiently, ensuring data quality and scalability.
• Algorithm Enhancement: Collaborate with data scientists to implement and optimize AI-driven matching algorithms that align remote workers with suitable job opportunities.
• Data Quality Assurance: Ensure data integrity, accuracy, and reliability by implementing robust validation and monitoring mechanisms.
• Performance Optimization: Analyze and optimize system performance, addressing bottlenecks and scaling challenges within our data infrastructure.
• Integration and Deployment: Work with cross-functional teams to deploy machine learning models into production environments efficiently and reliably.
• Technology Evaluation: Stay abreast of emerging technologies and best practices in data engineering and AI, recommending and implementing new tools and methodologies as appropriate.
• Collaboration: Partner with Product, Engineering, and Operations teams to understand data requirements and translate them into technical solutions.
• Documentation and Standards: Develop and maintain comprehensive documentation for data pipelines, systems architecture, and processes, ensuring compliance with industry standards.

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 in Python
• Big Data Technologies: Hands-on experience with big data frameworks and tools like Hadoop, Spark, or Kafka.
• Database Knowledge: Proficiency with relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases – Experience with MongoDB.
• Cloud Platforms: Experience with AWS.
• Data Modeling: Strong understanding of data modeling, schema design, and data warehousing concepts.
• 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.

Tagged as: remote, remote job, virtual, Virtual Job, virtual position, Work at Home, work from home