About the Role

We are looking for a motivated and curious Data Engineer to join our Data Platform team. In this role, you will work on building, optimizing, and maintaining the data systems that power analytics, reporting, and product features across the organization. This is an excellent opportunity for someone with strong SQL and Python skills who is eager to learn new technologies and grow in a fast-paced environment.

Key Responsibilities

• Design, develop, and maintain reliable data pipelines and ETL processes.
• Work with cross-functional teams to understand data needs and translate them into scalable data solutions.
• Write high-quality, optimized SQL queries for data extraction, transformation, and validation.
• Develop and maintain Python-based workflows, scripts, and automation.
• Ensure high standards of data quality, data integrity, and data availability.
• Participate in monitoring, troubleshooting, and improving data infrastructure for performance and reliability.
• Stay updated with new tools, frameworks, and best practices in the data ecosystem.

Basic Qualifications

• Strong proficiency in SQL (data manipulation, joins, aggregations, optimization).
• Solid hands-on experience with Python for data processing and automation.
• Strong problem-solving skills and a passion for building robust data systems.
• Eagerness to learn and adopt new technologies, tools, and methodologies.
• Strong analytical mindset with attention to detail.
• Good communication and collaboration skills.

Good to Have (Optional)

• Experience with cloud platforms (AWS, GCP, Azure).
• Familiarity with distributed data systems (Spark, Presto, Hive, Kafka, etc.).
• Knowledge of data modeling, warehouse concepts, or ELT tools.
• Exposure to CI/CD, Docker, or orchestration tools like Airflow.

Why Join Us?

• Opportunity to work on high-impact data problems at scale.
• Collaborative team culture with focus on learning and growth.
• Exposure to modern data engineering tools and technologies.
• A place where curiosity and initiative are valued.