Data Engineer

About the role:

We are seeking a highly skilled and experienced Senior Data Engineer to join our dynamic team. In this role, you will be responsible for designing, developing, and maintaining robust and scalable data pipelines and infrastructure, ensuring the efficient and reliable flow of data across various systems to support critical business operations and analytics.

Job Responsibilities:

• Design, build, and optimize data pipelines using various data integration tools and technologies (e.g., ETL, ELT, streaming) to ingest, transform, and load data from diverse sources into data warehouses, data lakes, and other data platforms.
• Develop and maintain data models, schemas, and data dictionaries to ensure data consistency, quality, and accessibility.
• Implement data governance policies and procedures to ensure data security, privacy, and compliance with regulatory requirements.
• Collaborate with data architects, data scientists, and business stakeholders to understand data requirements and translate them into technical solutions.
• Monitor data pipeline performance, troubleshoot issues, and implement optimizations to improve efficiency and reliability.
• Evaluate and recommend new data technologies and tools to enhance our data infrastructure and capabilities.
• Participate in code reviews, technical design discussions, and provide constructive feedback.
• Document data engineering processes, designs, and solutions.
• Assist in building and maintaining vector database pipelines and embedding generation jobs under senior guidance
• Support to deliver processing and chunking workflows that feed AI knowledge bases and RAG pipelines
• Build, test and monitor semantic search / retrieval quality for AI‑facing data layer undefined

Experience and Qualifications:

• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field. Master's degree preferred.
• Minimum of 5 to 9 years of experience in data engineering, with a strong focus on data
• Solid hands-on experience in building data pipelines on modern data architectures including Data Warehouse, Lakehouse, and batch/real-time data processing systems.
• Working AI knowledge base concepts: vector databases, embeddings, and semantic search is a plus
• Hands-on RAG pipeline components such as document chunking, embedding generation, and retrieval is a plus
• Good experience on building data layers that support LLM / AI agent use cases is a plus.
• Experience with relational databases (e.g., SQL Server, Oracle, PostgreSQL)
• Experience with big data technologies (e.g., Hadoop, Spark).
• Experience with containerization platforms such as OpenShift Container Platform (OCP) or Kubernetes
• Knowledge of DevOps practices, CI/CD pipelines
• Familiarity with data governance principles and best practices.
• Excellent problem-solving, analytical, and communication skills.
• Ability to work independently and collaboratively in a fast-paced environment.