Algotale( Lumiq.Ai) - Data Engineer (Python)
Job Title: Data Engineer
Experience: 5+ Years
Location: Mumbai / Noida
Job Overview
We are looking for a skilled Data Engineer with strong expertise in Python (OOPs), Airflow, and Snowflake to design and build scalable data pipelines and backend components for data platforms. The ideal candidate should have experience in building robust data engineering solutions and ensuring data quality across large datasets.
Key Responsibilities
Design, develop, and maintain scalable data pipelines and backend data services using Python.
Build modular and reusable components using Object-Oriented Programming (OOP) principles.
Develop and manage workflow orchestration using Apache Airflow.
Work with Snowflake to design efficient data models, optimize queries, and manage data warehousing solutions.
Implement data validation and data quality checks across large datasets.
Collaborate with data analysts, data scientists, and product teams to deliver reliable data solutions.
Monitor, troubleshoot, and optimize data pipelines for performance and reliability.
Maintain documentation for data workflows, pipelines, and architecture.
Required Skills
5+ years of experience in Data Engineering or related roles
Strong proficiency in Python with emphasis on OOP concepts
Experience building backend applications or SDKs using Python
Hands-on experience with Apache Airflow
Strong understanding of Snowflake architecture and concepts
Experience designing and managing data pipelines
Strong communication skills (8/10 - Mandatory)
Nice to Have
Experience implementing Data Quality frameworks
Hands-on experience with Great Expectations
Experience performing data quality checks on large datasets
Advanced experience working with Snowflake
Education
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
Preferred Candidate Traits
Strong problem-solving and analytical skills
Ability to work in a fast-paced and collaborative environment
Attention to detail with focus on data accuracy and reliability
