Posted on: 14/10/2025
Developer - Data Engineering & Cloud Analytics.
Role Overview :
Responsible for building, maintaining, and optimizing large-scale data pipelines and analytics solutions leveraging Snowflake, Kafka, Splunk, Airflow, AWS, Apache Iceberg, and Presto.
The candidate will bring hands-on development skills and collaborate with architects, analysts, and DevOps teams to deliver reliable, efficient, and scalable data services.
Key Responsibilities :
- Develop and maintain ETL/ELT pipelines using Airflow, orchestrating data movement across Snowflake, AWS, Iceberg, and Kafka systems.
- Implement and optimize real-time data ingestion and streaming solutions using Apache Kafka, ensuring high throughput and fault tolerance.
- Integrate Apache Iceberg and Presto for interactive analytics on large-scale data lakes.
- Write SQL, Python, and/or Scala code for complex data transformations, metric calculations, and business logic deployment.
- Collaborate with data architects to evolve data models and ensure alignment with enterprise best practices.
- Utilize Splunk for operational monitoring, log analysis, and incident troubleshooting within data workflows.
- Deploy and manage infrastructure on AWS (S3, EC2, Glue, Lambda, IAM), focusing on automation, scalability, and security.
- Document pipelines, produce clear runbooks, and share technical knowledge with team members.
Required Skills & Experience :
- 4 to 6 years of hands-on development experience with modern data stack components: Snowflake, Apache Kafka, Airflow, and AWS.
- Strong working knowledge of scalable SQL (preferably Snowflake, Presto) and scripting (Python/Scala).
- Experience implementing data lake solutions with Apache Iceberg.
- Familiarity with Splunk for monitoring and event management.
- Proven history of building, deploying, and troubleshooting ETL/ELT data flows and real-time streaming jobs.
- Knowledge of IAM, networking, and security concepts on AWS.
Preferred Qualifications :
- Bachelor's degree in Computer Science, Engineering, or related field.
- Experience in cloud-native data warehousing, cost optimization, and compliance.
- Certifications in AWS, Snowflake, or other relevant technologies.
This role is ideal for candidates who enjoy end-to-end work on cloud-native analytics platforms, working with cutting-edge data streaming and lakehouse technologies in production environments.
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Posted By
Posted in
Data Engineering
Functional Area
Data Engineering
Job Code
1560099
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