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
SYNECHRON’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.