Data Engineer / ETL Engineer

Description

abra professional services is seeking for an Data Engineer.

🔹 Key Responsibilities:

• Design, implement, maintain, and optimize ETL processes using Informatica.
• Build efficient data pipelines for data ingestion, cleansing, and transformation across multiple data sources.
• Work with various analytical databases.
• Collaborate closely with BI, Analytics, and Product teams to create decision-support data layers.
• Lead the process of onboarding and integrating data sources into relevant AI systems.
• Provide ongoing support for existing data infrastructures while participating in the implementation of new solutions.
• Ensure compliance with data quality standards, information security policies, and regulatory requirements.

Please note: This role requires a Data Engineer background.

Requirements

must have:

• Academic degree holder with a Bachelor’s degree in Computer Science, or a certified Practical Engineer (Technician) graduate in Computer Studies,
• or completion of Information Systems courses totaling at least 300 hours,
• or at least 5 years of general experience in the computing/IT field.
• At least 8 years of relevant experience in the BI (Business Intelligence) domain.

At least 5 years of experience out of the last 7 years in the following areas:

• Serving in a Data Engineer role.
• Establishment and development of Data Lake and DWH (Data Warehouse) environments.
• Data modeling.
• Design and implementation of DWH and Data Lake architectures.
• AI solution architecture.
• Design and implementation of data pipelines.
• Python development.
• Working with BI systems.
• Working with DWH-supported data models.
• Very high-level proficiency in SQL.
• Design and implementation of ETL processes using Informatica or equivalent ETL tools.

🔹 Additional Requirements – Advantages:

• Relevant academic degree in Information Systems, Computer Science, Engineering, or a related field – an advantage.
• Experience working with various analytical databases – an advantage.
• Experience with AI systems – an advantage.
• Familiarity with Data Governance and Data Quality processes.
• Proven knowledge and experience with Python.
• Previous experience working with Tableau in a production environment.