Data Engineer Junior
Role details
Job location
Tech stack
Job description
We are seeking a Junior Data Engineer to support the development and optimization of scalable data pipelines in a cloud-based environment. The role focuses on hands-on ETL development, big data processing, and contributing to critical initiatives such as Databricks migration and fraud analytics., * Design, build, and maintain scalable ETL and streaming data pipelines.
- Develop data processing solutions using Spark (PySpark or Java).
- Work with AWS cloud services (EMR, Lambda, S3, RDS) for data ingestion and processing.
- Collaborate with cross-functional teams to support fraud analysis and generate actionable insights for strategy teams.
- Contribute to Databricks migration initiatives and optimize existing workflows.
- Perform hands-on data engineering tasks including scripting, debugging, and pipeline enhancements.
Requirements
- 3+ years of hands-on experience in data engineering or related field.
- Strong experience with Spark (PySpark preferred) and ETL/streaming pipeline development.
- Proficiency in Python (preferred) or Java.
- Experience with AWS cloud services such as EMR, S3, Lambda, and RDS.
- Hands-on experience with Databricks.
- Solid understanding of data pipelines and distributed data processing.
Preferred Qualifications (Nice to Have)
- Experience with Airflow for workflow orchestration.
- Proficiency in UNIX/Linux and Shell scripting.
- Experience using Terraform for infrastructure as code.
- Exposure to machine learning or Large Language Models (LLMs) and related use cases.
Basic Requirements
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field.
Formal training or certification in software engineering concepts.
What We're Looking For
Strong problem-solving skills and attention to detail
Hands-on experience with ETL and big data workflows
Ability to work in a fast-paced, collaborative environment