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.