Data Engineer (Python) - Immediate Joining (3 Months)
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Key skills for this role
Role Overview
The employer is seeking an experienced Data Engineer with 5–6 years of experience designing, developing, and maintaining scalable data solutions.
The role supports inventory optimization, master data management, backend services, and business-critical data applications.
Key Skills for This Role
Full Job Posting
Role overview
The employer is seeking an experienced Data Engineer with 5–6 years of experience designing, developing, and maintaining scalable data solutions.
The role supports inventory optimization, master data management, backend services, and business-critical data applications.
Key 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 SQL queries and data models in BigQuery.
- Develop and integrate APIs for data exchange between systems.
- Implement ingestion frameworks from internal and external sources.
- Perform data cleansing, transformation, and validation.
- Maintain master data management processes.
- Support inventory optimization through data processing and business logic.
- Build backend services for data-driven applications.
- Monitor and troubleshoot pipelines for reliability and performance.
- Collaborate with Product, Analytics, and Engineering teams and follow data governance practices.
Technical requirements
- 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 and integration.
- Experience designing scalable ETL/ELT pipelines and working with large-scale datasets.
- Strong understanding of data modeling, data transformation, and database concepts.
- Proficiency with version control systems such as Git.
Preferred qualifications
- Experience with PySpark and distributed data processing.
- Basic understanding of machine learning concepts and workflows.
- Familiarity with data quality frameworks and validation practices.
- Experience with Docker, CI/CD, DevOps practices, and cloud-based data environments.
- Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field.
- Strong analytical, problem-solving, communication, and collaboration abilities.
- Experience with enterprise-scale data platforms and data-driven applications.
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