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2 days ago
As a key member of our team, you will be responsible for designing, building, and maintaining large-scale data systems to support business objectives. Your expertise in cloud-based technologies, particularly in data warehousing and transformation, will enable us to make informed decisions and drive growth.
Key Responsibilities:- Design and implement high-performance data pipelines with scalability, reliability, and speed.
- Lead end-to-end software development projects involving large language models and retrieval-augmented generation frameworks.
- Champion modern software engineering practices such as CI/CD, infrastructure-as-code, containerization, and cloud-native deployments.
Additionally, you will work closely with business stakeholders to transform use cases into production-ready services and solutions, owning systems from concept to production. This includes implementing rigorous testing and monitoring practices to ensure superior data quality and integrity.
Requirements:- 5–7 years of total professional experience.
- 3–5 years of experience in Data Engineering or a related discipline with a proven track record of success.
- Expertise in Python and SQL with strong data manipulation and analysis skills.
- Proficiency with Databricks/PySpark and dbt for data warehousing and transformation.
- Hands-on experience with workflow orchestration tools (e.g., Airflow, Temporal).
- Experience working with LLMs, prompt engineering, RAG frameworks, and vector databases.
To succeed in this role, you should have strong communication skills, both verbal and written, and the ability to handle large-scale data projects including ETL, data cleaning, and information retrieval. If you are passionate about innovative technology and solving complex problems, we encourage you to apply for this exciting opportunity.
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