- Job Title: Data Engineer for Data Platform Delta Lake House Project
- Project Involvement:
- Working on the Data Platform Delta Lake House for Meal and Rest Break KPIs
- Improvements on Tempo Rapid Bus Service On-Time
- Real-time On-Time, Bus Pullout and Bi-directional Logon data streaming
- Handling other backlog Data as a Service requests

- Skills Required:
- Proficiency in Python or R, and SQL
- Experience with ETL, handling large datasets, Lambda and Kappa Architecture
- Expertise in AWS and Azure, knowledge in GCP is a plus
- Understanding of Data Architecture and Workflow Automation
- Experience with Machine Learning Frameworks such as TensorFlow, PyTorch, Keras, Scikit-learn
- Knowledge in Statistics, probability, linear algebra, data cleaning and preprocessing
- Understanding of Deep Learning techniques like CNNs, RNNs, Transformers, GANs, and VAEs
- Familiarity with NLP and Computer Vision libraries such as Hugging Face, SpaCy, OpenCV
- Experience in Model Deployment and MLOps, using tools like TensorFlow Serving, TorchServe, FastAPI, MLflow, Kubeflow
- Familiarity with Cloud AI Services like AWS SageMaker, Azure Machine Learning, GCP AI Platform
- Educational Background:
- Bachelor's Degree in Computer Science, Information Technology, Data Science, Software Engineering
- Advanced Degrees in Cloud Computing, Data Engineering, or related fields is a plus
- Core Technical Skills:
- Proficiency in languages like Python, Java, Scala, and SQL
- Experience with scripting languages such as Bash or PowerShell
- Expertise in cloud platforms like AWS, Microsoft Azure, or Google Cloud Platform (GCP)
- Knowledge of Azure Synapse, Data Brick, Apache Hadoop, Spark, Kafka, Hive, and HBase
- Experience with Snowflake, Redshift, BigQuery, or similar platforms
- Proficiency with relational (SQL Server, Oracle) and NoSQL databases (MongoDB, Cassandra)
- Expertise in building data pipelines using tools like Apache Airflow, Apache Nifi, or cloud-native ETL services
- Experience with Terraform, CloudFormation, or Ansible to automate cloud infrastructure deployment
- Proficiency with Docker and Kubernetes for deploying scalable applications
- Analytical and Data Skills:
- Designing and implementing efficient data models
- Experience with Tableau, Power BI
- Understanding of how to prepare data for machine learning workflows
- Optimizing data storage, retrieval, and processing pipelines
- Certifications:
- AWS Certified Data Analytics - Specialty
- Google Professional Cloud Data Engineer
- Microsoft Certified: Azure Data Engineer Associate
- Cloudera Certified Professional: Data Engineer (CCP-DE)
- Experience:
- Deep understanding of business domains (e.g., e-commerce, finance, healthcare)
- Demonstrated ability to lead complex cloud-based data projects
- 5+ years in data engineering or a related field with increasing levels of responsibility
- Soft Skills:
- Strong problem-solving and critical thinking abilities
- Excellent communication skills to collaborate with cross-functional teams
- Project management experience to oversee large-scale data initiatives
- Adaptability to work in fast-paced and dynamic environments.