AI & Data Engineering Architect
Apetan Consulting
yesterday
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
EnglishJob location
Remote
Tech stack
Artificial Intelligence
Amazon Web Services (AWS)
Azure
Big Data
Computer Programming
Continuous Integration
Data Architecture
Information Engineering
Data Governance
ETL
Data Systems
Data Visualization
Hadoop
Python
Machine Learning
NoSQL
Power BI
TensorFlow
SQL Databases
Data Streaming
Tableau
Google Cloud Platform
PyTorch
Spark
Generative AI
Containerization
Data Lake
Kubernetes
Information Technology
Apache Flink
Kafka
Data Management
Machine Learning Operations
Data Pipelines
Docker
Job description
- Design and implement end-to-end data architecture and AI solutions.
- Define data pipelines, data models, and data governance frameworks.
- Lead development of scalable data platforms (data lakes, warehouses, lakehouses).
- Architect and deploy AI/ML models in production environments.
- Collaborate with data engineers, data scientists, and business stakeholders.
- Select appropriate tools, technologies, and frameworks for data and AI initiatives.
- Ensure data quality, security, and compliance standards are met.
- Guide teams on best practices for data engineering and MLOps.
- Optimize performance, scalability, and cost of data systems.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, or related field.
- Strong expertise in data platforms (SQL/NoSQL databases, data lakes, warehouses).
- Experience with cloud platforms (AWS, Azure, or Google Cloud Platform).
- Knowledge of ETL/ELT pipelines and big data technologies (Spark, Hadoop).
- Experience with AI/ML frameworks (TensorFlow, PyTorch, or similar).
- Strong programming skills (Python, SQL, or Scala).
- Experience with data modeling, governance, and security., * Experience with real-time/streaming data (Kafka, Flink).
- Familiarity with BI and visualization tools (Power BI, Tableau).
- Knowledge of MLOps, CI/CD pipelines, and containerization (Docker, Kubernetes).
- Exposure to Generative AI and NLP use cases., * Strategic thinking and architecture design
- Leadership and mentoring skills
- Problem-solving and analytical mindset
- Strong communication and stakeholder management
