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.