Developer – Data Engineering & Cloud Analytics

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.