Junior Data Engineer

Junior Data Engineer - Jordan Office

Job Overview

As a Junior Data Engineer at Ligadata, you will support the development, maintenance, and monitoring of data pipelines and Big Data solutions. You will work with senior engineers and cross-functional teams to ensure reliable data processing, data quality, and timely delivery.

The role requires a good foundation in SQL, Linux, Shell scripting, data analysis, and Big Data technologies, with a strong willingness to learn and troubleshoot within a production data environment.

Responsibilities

• Develop and maintain ETL/ELT data pipelines.


• Write and optimize SQL queries for data processing, validation, and analysis.


• Support data workflows using Apache Airflow.


• Work with Big Data technologies such as Hadoop, HDFS, Hive, Spark, Presto/Trino, Kafka, and HBase.


• Perform data validation, reconciliation, and data-quality checks.


• Develop scripts and automation using Shell/Bash and Python.


• Monitor data pipelines and assist in troubleshooting job failures and production issues.


• Work with structured and semi-structured data formats such as Parquet, JSON, CSV, and Avro.


• Support applications and data workloads running on Kubernetes (K8s).


• Analyze data to identify inconsistencies, anomalies, and operational issues.


• Participate in code reviews, documentation, and continuous improvement activities.


• Collaborate with senior engineers, DevOps, QA, database, and analytics teams.


• Use AI-assisted engineering tools to support development, troubleshooting, documentation, and data analysis while validating generated results before use.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.


• 1–3 years of experience in Data Engineering, Big Data, Software Engineering, or a related role.


• Good knowledge of SQL and relational database concepts.


• Good understanding of Linux and Shell/Bash scripting.


• Basic knowledge of the Hadoop ecosystem, including HDFS and Hive.


• Familiarity with Spark, Presto/Trino, and Apache Airflow.


• Basic understanding of Kafka and distributed data-processing concepts.


• Familiarity with Kubernetes and containerized environments.


• Knowledge of at least one programming language, preferably Python, Scala, or Java.


• Basic understanding of ETL/ELT, data warehousing, data quality, and data analysis.


• Familiarity with Git and software-development practices.


• Knowledge and practical experience using AI tools such as ChatGPT, GitHub Copilot, or similar tools for engineering tasks.


• Good analytical, troubleshooting, and problem-solving skills.


• Strong willingness to learn and develop technical skills.


• Good communication and teamwork skills.


• Self-motivated with a strong sense of ownership.