Ascendion - Senior Data Engineer

Overview

We are seeking an experienced Data Engineer Agentic AI (5 to 9 years) to design, develop, and optimize data pipelines and agentic AI solutions in modern cloud environments. This role demands strong engineering fundamentals, cloud-native expertise, and hands-on involvement in AI/ML and emerging multi?agent AI frameworks. The ideal candidate excels in cross-functional collaboration, thrives in agile environments, and communicates complex ideas effectively.

Key Responsibilities

Data Engineering & Pipeline Development :

• Design, build, and optimize scalable data engineering solutions in Azure/GCP cloud environments.
• Develop secure and reliable ETL/ELT pipelines using Python, PySpark, SQL, and UNIX/Linux scripting.
• Apply expertise in query optimization, data structures, transformations, metadata management, dependency tracking, and workload orchestration.
• Automate workflows using orchestration and scheduling tools.
  
  

• Kubernetes, containerized services, cluster management, cloud storage, and workspace management.
• Build and maintain CI/CD pipelines following DevOps best practices.
• Collaborate effectively using Git-based version control in multi-developer environments.
  
  

• Feature engineering, model deployment, and MLOps platform integrations.
• Work with AI/ML frameworks such as TensorFlow, PyTorch, and libraries like scikit-learn, MLflow.
• Build solutions using multi-agent AI tech stacks, including :
  
  

i. PydanticAI

ii. LangChain

iii. LangGraph

• Exposure to Agent-to-Agent Protocol or Model Context Protocol (MCP) is highly desirable.
• Cross-functional Collaboration & Agile Delivery
• Partner with data scientists, ML engineers, architects, and business teams.
• Translate complex technical concepts for non-technical stakeholders.
• Participate in Agile ceremonies within Scrum or Kanban frameworks.
  
  

• Track and manage work effectively using the ServiceNow ticketing system.
• Ensure performance, scalability, and operational excellence across data and AI systems.
  
  

• 5 to 9 years of experience in data engineering or related roles.
• Strong hands-on programming in Python, PySpark, SQL, and UNIX/Linux scripting.
• Proven experience designing and deploying data solutions in Azure or GCP (cloud certification preferred).
• Strong understanding of query tuning, distributed computing, data modeling, and data lifecycle management.
  
  

• CI/CD pipelines and DevOps tools
• Containerization (Docker), Kubernetes
• Cloud-native compute and storage services
• Excellent communication and documentation skills.
• Experience with automation and orchestration tools (Airflow, Databricks, Prefect, etc.).
• Good understanding of modern API and microservice architectures.
• Knowledge of Agile methodologies (Scrum, Kanban).
  
  

(ref:hirist.tech)