Data Engineer

About the Role:
 

We are seeking a Senior Data Engineer with deep expertise in distributed data processing and cloud-native architectures. This is a unique opportunity to join a forward-thinking team that values technical excellence, innovation, and business impact. You will be responsible for designing, building, and maintaining scalable data solutions that power critical business decisions in a fast-paced B2C environment.

 

Responsibilities:
 

• Design, develop, and maintain robust ETL/ELT data pipelines using Apache Spark and AWS Glue
• Build Zero-ETL pipelines using AWS services such as Kinesis Firehose, Lambda, and SageMaker
• Write clean, efficient, and well-tested code primarily in Python and SQL
• Collaborate with data scientists, analysts, and product teams to ensure timely and accurate data delivery
• Optimize data workflows for performance, scalability, and cost-efficiency
• Integrate data from various sources (structured, semi-structured, and unstructured)
• Implement monitoring, alerting, and logging to ensure data pipeline reliability
• Contribute to data governance, documentation, and compliance efforts
• Work in an agile environment, participating in code reviews, sprint planning, and team ceremonies
   

Expected Qualifications:
 

• 5+ years of professional experience in data engineering
• Advanced proficiency in Apache Spark, Python, and SQL
• Hands-on experience with AWS Glue, Kinesis Firehose, and Zero-ETL pipelines
• Familiarity with AWS Lambda and SageMaker for serverless processing and ML workflows
• Experience with ETL orchestration tools such as Airflow or dbt
• Solid understanding of cloud computing concepts, especially within AWS
• Strong problem-solving skills and the ability to work independently and collaboratively
• Experience working in B2C companies or data-rich product environments
• Degree in Computer Science or related field (preferred but not required)
• Bonus: Exposure to JavaScript and data science workflows