Data Engineer (Remote)

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 learning.

Education & Certifications:

• Bachelor’s degree or higher in a STEM field (Computer Science, Math, Physics,
  
  
  

Engineering, or related), required.

• Advanced degree in Computer Science or related field, preferred.
  
  
  

Professional Experience

• 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.

• Experience in financial services or product development environments is a strong plus.
  
  
  

Technical Skills & Competencies

• 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.

• 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).