Data Engineer

Job Description

We are looking for 4-5years Data Engineer with strong experience in Spark (PySpark), SQL, and data pipeline architecture. You will play a critical role in designing, building, and optimizing data workflows that enable scalable analytics and real-time insights. The ideal candidate is hands-on, detail-oriented, and passionate about crafting reliable data solutions, while collaborating with cross-functional teams.

Job Requirement

• Strong expertise in Spark (PySpark).
• Proficiency in SQL (query optimization, performance tuning, complex joins).
• Hands-on experience in designing and architecting data pipelines.
• Excellent communication and collaboration skills.

Job Responsibilities

• Design and architect scalable and efficient data pipelines for batch and real-time processing.
• Develop and optimize solutions using Spark (PySpark) and SQL.
• Ensure data pipelines are reliable, maintainable, and well-tested.
• Work with stakeholders to understand business requirements and translate them into data-driven solutions.
• Collaborate with cross-functional teams to ensure data quality, availability, and performance.
• Stay updated with emerging data engineering tools and practices.

Benefits

• Innovative Engineering: Collaborative, fail-fast, flat hierarchy. Fosters learning, initiative, curiosity.
• Masterful Development: Emphasizes clean code, SOLID principles, TDD/BDD. Utilizes robust CI/CD and polyglot engineering.
• Continuous Growth: Structured mentorship, masterclasses, Geeknights, workshops, continuous skill enhancement, blog contributions.
• Agile & Client-Centric: Adopts Agile (Scrum, XP), promotes project ownership and deep client understanding for impactful solutions.
• Supportive Environment: Healthy work-life balance, flexible schedules, comprehensive benefits (generous leave), strong team-building.