Intellectsoft is a software development company delivering innovative solutions since 2007. We operate across North America, Latin America, the Nordic region, the UK, and Europe. We specialize in industries like Fintech, Healthcare, EdTech, Construction, Hospitality, and more, partnering with startups, mid-sized businesses, and Fortune 500 companies to drive innovation and scalability. Our clients include Jaguar Motors, Universal Pictures, Harley-Davidson, and many more where our teams are making daily impactTogether, our team delivers solutions that make a difference. Learn more at www.intellectsoft.net

Our customer's product is an AI-powered platform that helps businesses make better decisions and work more efficiently. It uses advanced analytics and machine learning to analyze large amounts of data and provide useful insights and predictions. The platform is widely used in various industries, including healthcare, to optimize processes, improve customer experiences, and support innovation. It integrates easily with existing systems, making it easier for teams to make quick, data-driven decisions to deliver cutting-edge solutions.

Requirements

• 5–6+ years of hands-on experience in Data Engineering.
• Strong proficiency in Python and advanced SQL, including query optimization, data modeling, and performance tuning.
• Deep understanding of distributed data processing frameworks, particularly Apache Spark.
• Strong practical experience with Apache Airflow for workflow orchestration and pipeline management.
• Working knowledge of backend application development frameworks such as FastAPI.
• Foundational understanding of LLMs, AI/GenAI concepts, and their practical applications within data platforms.
• Familiarity with modern AI and data infrastructure concepts, including:
• Vector Databases
• Semantic Search
• Knowledge Graphs
• Retrieval-Augmented Generation (RAG) architectures (preferred)
• Hands-on experience with at least one major cloud platform: AWS, Azure, or GCP.
• Hands-on experience with Git and CI/CD pipelines.

Responsibilities

• Design and build highly reliable and scalable data pipelines using PySpark and big data technologies.
• Collaborate with the data science team to develop new features that enhance model accuracy and performance.
• Create standardized data models to improve consistency across various deployments.
• Troubleshoot and resolve issues in existing ETL pipelines and optimize workflows.
• Conduct POCs to evaluate new technologies and integrate additional data sources.
• Follow and promote best practices for software development, ensuring high-quality solutions that meet requirements and deadlines.
• Document development updates and maintain clear technical documentation.

Benefits

• Employment-based cooperation
• Comprehensive insurance for you and your family (health, life, and accident)
• Paid PTO policy (vacation, sick leaves, and public holidays)
• Tech equipment provided
• Udemy courses, workshops, trainings & expert knowledge-sharing
• Flexible hours & work setup