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.