Responsabilidades
- Data Engineering: Design, develop, and maintain robust data pipelines to efficiently process large volumes of structured and unstructured data. Ensure data is clean, reliable, and accessible for downstream applications.
- Data Modeling: Develop and implement data models that support our AI-driven job matching algorithms. Work closely with data scientists and machine learning engineers to ensure data structures meet the analytical needs of the platform.
- ETL Processes: Build and manage ETL (Extract, Transform, Load) processes that move data from various sources into our data warehouse, ensuring that data is transformed correctly and efficiently.
- Data Warehousing: Architect and maintain scalable data warehousing solutions using technologies like PostgreSQL or ElasticSearch. Ensure that our data warehouse is optimized for performance and supports the rapid querying needs of our platform.
- Data Analytics: Collaborate with the analytics team to provide insights into user behavior, platform performance, and other key metrics. Ensure that data is readily available for analytics and reporting purposes.
- Big Data Technologies: Utilize big data technologies such as Hadoop and Spark to process and analyze large datasets. Optimize the performance of these technologies to handle JobLeap’s growing data needs.
- API Integration & Data Scraping: Work with APIs, data feeds, and scraping technologies to integrate external data sources into our platform. Ensure that data from these sources is accurate, timely, and aligns with our data quality standards.
- Collaboration: Work closely with cross-functional teams, including data scientists, product managers, and AI engineers, to understand data needs and translate them into technical solutions. Communicate complex technical concepts to non-technical stakeholders effectively.
- Problem Solving: Tackle complex data challenges, identifying bottlenecks and inefficiencies in our data processes, and implementing solutions to optimize performance.
Requisitos
- Fluency in English is required, with excellent communication skills to effectively collaborate in a remote, international team environment.
- Proven experience in Data Engineering and Data Modeling, with a strong track record of building scalable data solutions.
- Expertise in ETL processes, with hands-on experience in designing and optimizing data pipelines.
- In-depth knowledge of Data Warehousing and Data Analytics technologies, particularly PostgreSQL or Elasticsearch.
- Proficiency in programming languages such as Python, SQL, and experience with big data technologies like Hadoop and Spark.
- Experience with API integration, data feeds, and scraping technologies.
- Strong problem-solving and analytical skills, with a focus on optimizing data processes and systems.
- Excellent communication and collaboration skills, with the ability to work effectively in a remote, cross-functional team environment.
- Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
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