About the Role

As a Senior Data Engineer at Aspire, you will play a key role in designing, developing, and maintaining data workflows and pipelines, ensuring the efficient and reliable movement of data across various systems. You will work with modern data technologies including Apache Airflow, PySpark, Hive, AWS, and Snowflake, while collaborating with cross-functional teams to deliver high-quality data solutions. This role requires a strong focus on data quality, performance optimization, and adherence to security and compliance standards.

What You'll Do

Design, implement, and manage complex DAGs and SubDAGs in Apache Airflow.
Utilize Operators, macros, connections, variables, and XCom for efficient task execution.
Conduct unit testing to ensure the robustness of Airflow workflows.
Perform file operations and data movement between HDFS and S3 (and vice versa).
Manage Hive external tables, update table DDL, and handle partition operations.
Execute basic Hadoop commands and navigate/traverse HDFS.
Work with Hive on Tez for optimized query execution.




Utilize AWS command line tools for tasks such as listing and copying files from S3.
Implement and manage secrets using tools like Ansible Vault and AWS Secrets Manager.
Develop and optimize data processing tasks using PySpark.
Understand and leverage Livy for efficient Spark job execution.
Import and export data between Microsoft SQL Server and HDFS using Sqoop.
Apply dimension modeling principles, define facts and dimensions, and manage surrogate keys.
Implement effective branching strategies in Git.
Participate in the process of raising and reviewing Merge Requests in GitLab.
Utilize SSIS for migrating data workflows, ensuring a smooth transition.
Model data in Snowflake, differentiating between external and internal tables.
Understand the use of views and materialized views in Snowflake.

What You'll Need

Bachelor's degree in Computer Science, Information Technology, or a related field.
Proficient in Python (both

📌 Senior Data Engineer (Modena)
🏢 Aspire, Jordan
📍 Modena