Data & AI Engineer | Cloud-Native Pipelines, Python, Pandas, Large-Scale Data Processing, Cloud (AWS/Azure/GCP), Machine Learning Frameworks

Job Summary
Synechron is seeking an experienced Lead Python Data & AI Engineer to architect, develop, and optimize large-scale data pipelines and AI solutions. This role involves utilizing advanced Python, multi-threading, and data processing tools to support enterprise data science and machine learning initiatives. The successful candidate will collaborate across cross-functional teams to deliver scalable, secure data systems, integrating AI/ML workflows supported by containerization and cloud deployment, driving organizational innovation and operational excellence.

Software Requirements

• Required:

  
  

  • Extensive hands-on experience with Python (latest stable version recommended), including proficiency in multi-threading and object-oriented programming (OOP) design patterns

    
    

  • Practical knowledge of data processing libraries such as Pandas and familiarity with data storage formats such as Parquet and Delta Lake

    
    

  • Experience developing and maintaining data pipelines on cloud platforms (Azure, AWS, GCP) supporting AI/ML workflows

    
    

  • Experience with databases such as Oracle and ORM frameworks (SQLAlchemy, Django ORM) for database interaction and management

    
    

  • Proficiency with containerization tools like Docker and orchestration platforms such as Kubernetes for deployment

    
    

  • Strong understanding of CI/CD practices, automated testing (pytest), and version control (Git/GitHub) workflows

    
    

  • Knowledge of AI engineering tools such as GitHub Copilot, code assistants, or similar development aids

    
    

• Preferred:

  
  

  • Experience with cloud-native data services, data governance practices, and scalable architecture design

    
    

  • Knowledge of distributed systems, data streaming, and real-time processing frameworks

    
    

  • Familiarity with ML frameworks like TensorFlow, PyTorch, for integrating AI models into pipelines

    
    

Overall Responsibilities

• Design, build, and optimize scalable data pipelines using Python, Pandas, and cloud services for enterprise analytics and AI deployment

  
  

• Develop and maintain data workflows for large datasets, supporting data cleansing, feature engineering, and model inference processes

  
  

• Collaborate with data scientists, AI architects, and platform teams to facilitate seamless data and model integration

  
  

• Implement automation for data ingestion, processing, and system deployment using CI/CD pipelines and containerization

  
  

• Troubleshoot and resolve performance bottlenecks, optimize data storage/processing, and enforce data security standards

  
  

• Create technical documentation and design standards supporting data and AI workflows

  
  

• Lead initiatives on data governance, quality, and compliance across data pipelines and models

  
  

• Support innovation by evaluating new tools, cloud features, and AI techniques for organizational benefit

  
  

Technical Skills (By Category)

• Programming Languages:
  Required: Python (advanced), multi-threading, OOP design patterns
  Preferred: Additional languages such as Java or Scala for performance-critical components

  
  

• Data Management & Storage:
  Pandas, NumPy, Parquet, Delta Lake, SQL (Oracle, MySQL), ORM frameworks (SQLAlchemy, Django ORM)

  
  

• Cloud Technologies:
  AWS, Azure, or GCP cloud platforms supporting data pipelines, AI workflows, and storage

  
  

• Frameworks & Libraries:
  Pandas, TensorFlow, PyTorch, Spark (PySpark), ML frameworks (preferred for AI model deployment)

  
  

• Data Orchestration & Automation:
  Airflow, Terraform, Docker, Kubernetes, CI/CD tools (Jenkins, GitHub Actions)

  
  

• Security & Governance:
  Data encryption, access controls, compliance with enterprise security standards

  
  

Experience Requirements

• Minimum of 6 years of practical experience supporting data engineering, AI workflows, or large-scale data pipelines

  
  

• Proven expertise in Python automation, multi-threaded data processing, and cloud-based data solutions

  
  

• Strong experience deploying AI/ML models within scalable pipelines supported by containerized and cloud environments

  
  

• Demonstrated success working in agile teams supporting enterprise and data science initiatives

  
  

• Industry experience in finance, healthcare, or large enterprise data environments is preferred but not mandatory

  
  

Day-to-Day Activities

• Develop, deploy, and optimize large-scale data pipelines supporting enterprise analytics and AI workloads

  
  

• Implement batch and streaming data workflows, feature engineering, and model inference pipelines

  
  

• Collaborate with data scientists, ML engineers, and platform teams for seamless data integration and deployment

  
  

• Automate data workflows, infrastructure provisioning, and model deployment using DevOps practices

  
  

• Troubleshoot pipeline performance issues, optimize storage and processing, and ensure data governance compliance

  
  

• Document data architecture, model workflows, procedures, and best practices

  
  

• Evaluate emerging data/AI tools, integrate new frameworks, and contribute to innovation initiatives

  
  

Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, or related fields

  
  

• 6+ years supporting data pipelines, AI models, and large-scale data environments on cloud platforms

  
  

• Certifications in cloud (AWS, Azure, GCP), data engineering, or ML frameworks are advantageous

  
  

• Demonstrated expertise in Python, Pandas, data processing, and cloud-native data architecture support

  
  

Professional Competencies

• Analytical mindset with strong problem-solving skills for complex data and AI system issues

  
  

• Effective communication skills for cross-team collaboration and stakeholder engagement

  
  

• Leadership qualities to mentor junior team members and promote best practices

  
  

• Strategic thinking regarding data governance, security, and scalable architecture

  
  

• Adaptability to new AI/ML tools, cloud features, and data management trends

  
  

• Time management skills to prioritize tasks and deliver impactful solutions within deadlines

  
  

S​YNECHRON’S DIVERSITY & INCLUSION STATEMENT
 

Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.

All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

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