
BigStep Technologies
7 days ago
Key Responsibilities :
- Build, scale, and maintain robust data solutions to support business objectives.
- Design, implement, and optimize high-performance data pipelines (extraction, loading, transformation, and orchestration) with scalability, reliability, and speed.
- Lead end-to-end software development projects involving large language models (LLMs), retrieval-augmented generation (RAG) frameworks, and other AI technologies.
- Champion modern software engineering practices such as CI/CD, infrastructure-as-code, containerization, and cloud-native deployments.
- Collaborate with business stakeholders to transform use cases into production-ready services and solutions, owning systems from concept to production.
- Implement rigorous testing and monitoring practices to ensure superior data quality and integrity.
- Mentor and guide junior team members, fostering a culture of excellence and continuous & Certifications :
- Bachelors degree or higher in a STEM field (Computer Science, Math, Physics, Engineering, or related), required.
- Advanced degree in Computer Science or related field, Experience :
- 5 to 7 years of total professional experience.
- 3 to 5 years of experience in Data Engineering or a related discipline with a proven track record of success.
- Experience in financial services or product development environments is a strong Skills & Competencies :
- 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.
- Knowledge of machine learning fundamentals, feature engineering, and knowledge graphs is an advantage.
- Strong experience in designing and implementing complex data systems from scratch.
- Ability to handle large-scale data projects including ETL, data cleaning, and information retrieval.
- Strong communication skills (verbal and written).
(ref:hirist.tech)
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