Data Engineer Junior

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.

• 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