Data Engineer for AI Engineering Team Leader

hace 3 semanas


Barcelona, Barcelona, España Dow Jones A tiempo completo

About Our Organization

Dow Jones is a global leader in providing news and business information, delivering content to consumers and organizations worldwide through various formats. With over 130 years of experience, we have one of the largest news-gathering operations globally. We are home to prominent publications and products, including the flagship Wall Street Journal, Barron's, MarketWatch, and more.

Our Technology Team

Our technology team drives the evolution of our engineering, data, product, and user experience functions. We focus on delivering cutting-edge solutions that shape the digital landscape for our customers, readers, and users. From revolutionizing visuals to optimizing tools and harnessing the power of data, mobile, video, and social platforms, our team is committed to providing a seamless and immersive experience across all touchpoints.

About the Role

We are seeking an experienced Data Engineer to join our AI Engineering Team. As a key team member, you will play a crucial role in operationalizing data solutions to meet our organization's needs and deliver tangible value. You will leverage your strong data engineering skills to develop robust, secure, and scalable data pipelines, utilizing your expertise in data retrieval and processing techniques.

Your Responsibilities

  • Collaborate with data scientists and ML engineers to design, develop, and maintain end-to-end data pipelines for extraction, transformation, loading (ETL), and storage.
  • Clean, transform, and structure data using industry-standard techniques, ensuring quality and consistency.
  • Work with APIs to retrieve data from external sources or integrate with third-party services, adhering to best practices.
  • Manage and optimize SQL and NoSQL database systems for data storage, ensuring integrity and performance.
  • Automate data fetching, processing, and storage by implementing data pipelines for ML/AI use cases, leveraging ETL principles.
  • Identify and troubleshoot issues related to data quality and pipeline performance, applying problem-solving skills.
  • Communicate effectively with stakeholders and data providers to gather requirements and ensure project alignment.
  • Stay updated with industry trends, emerging technologies, and best practices in data engineering for Machine Learning.

Requirements

  • At least 3 years of industrial experience in a data engineering role.
  • Experience with cloud-based infrastructure and services (AWS, GCP preferred).
  • Experience in designing and implementing end-to-end data pipelines for ML/AI use cases.
  • Preferably in Airflow or GCP Cloud Composer.
  • Ability to work with APIs to retrieve data from external sources or integrate with third-party services.
  • Familiarity with NLP and Machine Learning frameworks and libraries (e.g., PyTorch, HuggingFace, LangChain, spaCy, NLTK, scikit-learn, etc.).
  • Experience with working on Jenkins and/or Docker.
  • Familiarity with database systems, including SQL and NoSQL databases.

About Us

Dow Jones is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law. We strongly encourage applications from all qualified individuals, including women, people with disabilities, and those from underrepresented groups.

Salary Estimate

The estimated salary for this role is $140,000 - $170,000 per year, based on national averages and industry standards.


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