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

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.