
Senior Data Engineer
2 weeks ago
Overview
Job Title: Senior Data Engineer (AWS & Confluent Data/AI Projects)
Work Set-up: Remote/WFH (open to Filipino citizens or permanent visa holders only)
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 .
- Must have AWS certification / AWS Certified
- 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, AzureDevOps, or similar).
- Must have a working laptop
- 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.
- 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, KafkaConnect, 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).
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