Senior Data Engineer (AWS & Confluent Data/AI Projects) | Remote

Work Set-up: Remote Schedule: 10am-6pm SGT 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). Required Skills and Qualifications: - Bachelor's or Master's degree in Computer Science, Software Engineering, or a related quantitative field. - 3 to 5 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). - AWS Certifications (e.g., AWS Certified Data Analytics - Specialty, AWS Certified Preferred Qualifications (Nice to Have): - 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. - Candidate must have a working laptop Originally posted on Himalayas