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DELTA SG CONSULTING is seeking a Senior Data Engineer to design, implement, and maintain robust data pipelines and scalable infrastructure. You will ensure reliable data flow across systems to support analytics and business operations in a fast-paced setting.
You will build data models, enforce governance, and collaborate with architects, scientists, and stakeholders to translate requirements into actionable solutions. Experience with AI-ready data layers is a plus.
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.
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
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.