At RavenPack, we are at the forefront of developing the next generation of generative AI tools for the finance industry and beyond. With 20 years of experience as a leading big data analytics provider for financial services, we empower our clients—including some of the world's most successful hedge funds, banks, and asset managers—to enhance returns, reduce risk, and increase efficiency by integrating public information into their models and workflows. Building on this expertise, we are now launching a new suite of GenAI and SaaS services, designed specifically for financial professionals.
Join a Company that is Powering the Future of Finance with AI
RavenPack has been recognized as the Best Alternative Data Provider by WatersTechnology and has been included in this year’s Top 100 Next Unicorns by Viva Technology. You will be working on Bigdata.com, a next-generation platform aimed at transforming financial decision-making.
We are seeking an experienced and highly motivated Senior Data Engineer to join our dynamic team. As a Senior Data Engineer, you will collaborate with Data Scientists and Analysts to understand data requirements and implement data pipelines and infrastructure to support our data-driven initiatives. You will play a crucial role in designing, developing, and maintaining innovative data solutions which will shape the future of our data ecosystem. Your ability to work across multiple disciplines, from software engineering to database management, will contribute to building robust and scalable solutions.
Responsibilities:
Develop data pipelines to extract, transform, and load (ETL) structured and unstructured data from various sources.
Collaborate with Data Analysts and Data Scientists to grasp requirements from specifications and translate them into technical solutions.
Implement monitoring tools to perform data quality checks and validation processes, ensuring data accuracy and integrity.
Maintain and optimize existing data infrastructure, ensuring the reliability, scalability, and performance of scheduled data pipelines and workflows.
Develop and maintain documentation related to data engineering processes.
Manage project tasks and ensure successful project delivery.
Requirements:
Bachelor's or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
3+ years of experience in data engineering or software engineering projects.
Advanced programming skills in Python for developing data processing pipelines.
SQL proficiency and experience working with relational databases (experience with NoSQL databases is a plus).
Experience with cloud platforms, such as AWS.
Experience with scripting languages like Bash for automation and scripting tasks.
Familiarity with containerization technologies, such as Docker.
Experience with Git.
Excellent problem-solving skills and ability to analyze complex data-related issues.
Attention to detail and a commitment to delivering high-quality solutions.
Strong communication skills and ability to collaborate effectively with cross-functional teams. Ability to communicate effectively in English, both in writing and verbally.
Desirable
Experience working with large datasets and big data technologies.
Familiarity with Machine Learning (ML) techniques and frameworks, as well as Large Language Model (LLM) technologies is highly desirable.
What's in it for You?
International Culture: With its headquarters in Marbella, Spain, and presence in New York and London, RavenPack takes pride in being a truly diverse global organization.
Competitive Salary: In RavenPack, we believe that your time and experience needs to be fairly rewarded.
Continuous learning: We provide the support needed to grow within the team.
Innovation: Innovation is the key to our success, so we encourage you to speak up and tell us about your vision.
Hybrid work arrangement
Shuttle bus: From Malaga, Fuengirola, La Riviera, and Estepona is available for free from the company.
Diversity is in our DNA! You will work in an international environment (over 29 nationalities and 24 languages spoken!)
