Senior Data Engineer (AWS & Confluent) - WFH/WAH/Remote

Job Title: Senior Data Engineer (AWS & Confluent Data/AI Projects)

Work Set-up: Remote/WFH (must be a Filipino citizen or a PH permanent resident) 

Shift Schedule: 10 am-6 pm SGT/PHT

Required Qualifications:

• Bachelor's degree in Computer Science, or a related quantitative field
  
• At least 3 years of experience in data engineering, with a significant focus on cloud-based solutions.
• Strong expertise in AWS data services (S3, Glue, EMR, Redshift, Kinesis, Lambda, etc.).
• Extensive hands-on experience with Confluent Platform/Apache Kafka for building real-time data streaming applications.
• Proficiency in programming languages such as Python, PySpark, Scala, or Java.
• Expertise in SQL and experience with various database systems (relational and NoSQL).
• Solid understanding of data warehousing, data lakes, and data modeling concepts (star schema, snowflake schema, etc.).
• Experience with CI/CD pipelines and DevOps practices (Git, Terraform, Jenkins, Azure DevOps, or similar).
• Must have a working laptop

Preferred Qualifications (Nice to Have):

• AWS Certifications (e.g., AWS Certified Data Analytics - Specialty, AWS Certified
• Solutions Architect - Associate/Professional
• Experience with other streaming technologies (e.g., Flink).
• Knowledge of containerization technologies (Docker, Kubernetes).
• Familiarity with Data Mesh or Data Fabric concepts.
• Experience with data visualization tools (e.g., Tableau, Power BI, QuickSight).
• Understanding of MLOps principles and tools.

Responsibilities:

• Architect and Design Data Solutions: Lead the design and architecture of scalable, secure, and efficient data pipelines for both batch and real-time data processing on AWS. This includes data ingestion, transformation, storage, and consumption layers.
• Confluent Kafka Expertise: Design, implement, and optimize highly performant and reliable data streaming solutions using Confluent Platform (Kafka, ksqlDB, Kafka Connect, Schema Registry). Ensure efficient data flow for real-time analytics and AI
  applications.
• AWS Cloud Native Development: Develop and deploy data solutions leveraging a wide range of AWS services, including but not limited to:
• Data Storage: S3 (Data Lake), RDS, DynamoDB, Redshift, Lake Formation.
• Data Processing: Glue, EMR (Spark), Lambda, Kinesis, MSK (for Kafka integration).
• Orchestration: AWS Step Functions, Airflow (on EC2 or MWAA)
• Analytics & ML: Athena, QuickSight, SageMaker (for MLOps integration).