Senior Full stack Data Engineer

About the Role

We are looking for a Full Stack Data Engineer to design, build, and maintain scalable data platforms and pipelines. The ideal candidate has strong hands-on experience across data ingestion, transformation, orchestration, and cloud-based analytics, with a focus on modern lakehouse architectures.

Key Responsibilities

• Design, develop, and maintain end-to-end data pipelines using Python, PySpark, and SQL
• Build and optimize data transformation workflows using dbt on Snowflake
• Develop scalable lakehouse architectures for structured and semi-structured data
• Implement reliable data ingestion frameworks using Kafka, AWS Glue, and custom connectors
• Orchestrate workflows and manage dependencies using Apache Airflow
• Manage cloud infrastructure on AWS (S3, Glue, EMR, Redshift/Snowflake integrations)
• Implement Infrastructure as Code (IaC) using Terraform
• Collaborate with cross-functional teams to deliver analytics-ready datasets
• Ensure data quality, performance optimization, and cost efficiency
• Use GitLab for version control, CI/CD, and collaborative development
• Monitor, troubleshoot, and resolve data pipeline issues in production environments

Requirements

Required Skills & Qualifications

• 4+ years of experience with AWS data services and cloud-based data engineering
• Strong programming skills in Python and PySpark
• Hands-on experience with Snowflake and dbt for data modeling and transformations
• Solid understanding of SQL for complex analytical queries
• Experience with Apache Airflow for workflow orchestration
• Proficiency in Kafka for real-time/streaming data ingestion
• Experience with AWS Glue/ Airflow for ETL development
• Experience with Terraform for infrastructure automation
• Strong experience with GitLab and CI/CD pipelines