Data Engineer (Python) - Immediate Joining (3 Months)

Müller's Solutions; Dhahran Compound; On-site; SAR 230,000 - 340,000; Full time

Job summary

Muller's Solutions is seeking an experienced Data Engineer with 5-6 years of experience to design, develop, and maintain scalable data solutions. The ideal candidate will excel in Python, Pandas, NumPy, Airflow, BigQuery, SQL, and API development, and will build robust data pipelines for inventory optimization and backend services.

You will collaborate with Product, Analytics, and Engineering teams, implement data governance, and ensure data quality and performance across large datasets.

Qualifications

• 5-6 years of experience in Data Engineering or related roles.
• Strong hands-on experience with: Python, Pandas, NumPy, Apache Airflow, Google BigQuery, SQL, and API development.
• Experience designing and implementing scalable ETL/ELT pipelines.
• Strong understanding of data modeling, data transformation, and database concepts.
• Experience working with large-scale datasets and optimizing query performance.
• Proficiency with Git.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for data ingestion and processing.
• Build and optimize data workflows using Apache Airflow.
• Develop data processing solutions using Python, Pandas, and NumPy.
• Design and optimize complex SQL queries and data models in BigQuery.
• Develop and integrate APIs to support data exchange between systems.
• Implement data ingestion frameworks from various internal and external sources.
• Perform data cleansing, transformation, and validation to ensure data accuracy and consistency.
• Develop and maintain processes for master data management.
• Support inventory optimization initiatives by implementing data processing and business logic.
• Build and maintain backend services that enable data‑driven applications.
• Monitor and troubleshoot data pipelines to ensure reliability and performance.
• Collaborate with cross‑functional teams, including Product, Analytics, and Engineering teams.
• Ensure adherence to data governance, security, and best practices.

Skills

Python

Pandas

NumPy

Apache Airflow

Google BigQuery

SQL

API development

ETL/ELT pipelines

Data modeling

Git

Education

Bachelor's degree in Computer Science, Information Technology, Data Science, or related field

Tools

Docker

Job description

Muller's Solutions is seeking an experienced Data Engineer with 5-6 years of experience in designing, developing, and maintaining scalable data solutions. The ideal candidate should possess strong expertise in Python, Pandas, NumPy, Airflow, BigQuery, SQL, and API development. The candidate will play a key role in building robust data pipelines, processing large datasets, and supporting business‑critical applications related to inventory optimization, master data management, and backend services.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines for data ingestion and processing.
• Build and optimize data workflows using Apache Airflow.
• Develop and maintain data processing solutions using Python, Pandas, and NumPy.
• Design and optimize complex SQL queries and data models in BigQuery.
• Develop and integrate APIs to support data exchange between systems.
• Implement data ingestion frameworks from various internal and external sources.
• Perform data cleansing, transformation, and validation to ensure data accuracy and consistency.
• Develop and maintain processes for master data management.
• Support inventory optimization initiatives by implementing data processing and business logic.
• Build and maintain backend services that enable data‑driven applications.
• Monitor and troubleshoot data pipelines to ensure reliability and performance.
• Collaborate with cross‑functional teams, including Product, Analytics, and Engineering teams.
• Ensure adherence to data governance, security, and best practices.

Requirements

Technical Requirements

Must‑Have Skills

• 5-6 years of experience in Data Engineering or related roles.
• Strong hands‑on experience with:
  • Python
  • Pandas
  • NumPy
  • Apache Airflow
  • Google BigQuery
  • SQL
  • API development and integration
• Experience in designing and implementing scalable ETL/ELT pipelines.
• Strong understanding of data modeling, data transformation, and database concepts.
• Experience working with large‑scale datasets and optimizing query performance.
• Proficiency with version control systems such as Git.

Good‑to‑Have Skills

• Experience with PySpark and distributed data processing.
• Basic understanding of Machine Learning concepts and workflows.
• Familiarity with data quality frameworks and data validation practices.
• Experience with Docker and containerization technologies.
• Knowledge of CI/CD pipelines and DevOps practices.
• Experience working in cloud‑based data environments.

Preferred Qualifications

• Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.
• Strong analytical and problem‑solving skills.
• Excellent communication and collaboration abilities.
• Experience working on enterprise‑scale data platforms and data‑driven applications.