Data Systems Engineering Manager – Python

Data Systems Engineering Manager – Python

Experience:

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Mode of Engagement:

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Educational Qualification:

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What We Are Looking For:

• 7–12 years of experience in

  managing end-to-end data systems

  , including

  data collection, API-driven data delivery, and AI model integrations

  . 
• Proven expertise in

  Python-based data engineering

  ,

  data scraping

  , and

  pipeline orchestration

  for large-scale analytics and automation projects. 
• Strong background in

  building scalable APIs

  ,

  microservices

  , and

  data pipelines

  using Python, Docker, and Kubernetes. 
• Experience in

  customizing open-source language models (LLMs)

  and integrating them into enterprise solutions. 
• Proficiency in

  AWS cloud services

  ,

  PostgreSQL/MySQL

  ,

  CI/CD

  , and

  DevOps tools

  for continuous delivery and monitoring. 
• Ability to lead distributed engineering teams, manage delivery timelines, and drive innovation through automation and AI-driven workflows. 

Responsibilities:

• Lead and mentor engineering teams responsible for designing, implementing, and maintaining

  data ingestion, transformation, and delivery pipelines

  . 
• Architect

  data systems

  combine scraping, big data processing, and AI-based enrichment to support analytics and product intelligence. 
• Oversee

  API architecture

  and

  system scalability

  , ensuring high performance and secure data flow across services. 
• Manage

  public data scraping

  and

  data integration

  projects that involve large, unstructured datasets and complex relational mappings. 
• Drive

  AI model customization

  using open-source frameworks (LangChain, LlamaIndex, or custom LLM integrations) to improve automation and search intelligence. 
• Collaborate with product managers, AI teams, and data analysts to translate requirements into actionable data engineering tasks. 
• Implement and monitor

  data quality, governance, and compliance standards

  throughout the data lifecycle. 
• Optimize deployment processes using

  Docker, Kubernetes, AWS Lambda, and CI/CD pipelines

  . 
• Conduct regular technical reviews, mentor developers, and establish best practices for Python, cloud deployment, and automation. 

Qualifications:

• Bachelor's or master's degree in computer science, Engineering, or related field. 
• Hands-on expertise in

  Python, Django, FastAPI, SQL, and API-driven system design

  . 
• Strong understanding of

  data pipelines, scraping frameworks (BeautifulSoup, Scrapy), and distributed data systems

  . 
• Experience with

  AI/LLM integration, automation frameworks

  , and data-driven architecture design. 
• Proficiency in

  AWS cloud ecosystem

  ,

  Docker

  ,

  Kubernetes

  , and

  Git-based CI/CD

  workflows. 
• Demonstrated leadership in managing multi-member engineering teams and delivering enterprise-grade products. 
• Excellent analytical, communication, and problem-solving abilities. 
• Familiarity with

  Agile methodologies, Jira/ClickUp

  , and project management best practices.