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