We are seeking a highly motivated and responsible Data Engineer to join our dynamic team. This role requires hands-on experience in building scalable data pipelines, managing structured and unstructured databases, and supporting end-to-end data operations. The ideal candidate will bring strong problem-solving skills, a collaborative mindset, and a commitment to data excellence.

• Design, develop, and manage reliable and scalable data pipelines.
• Clean, validate, and transform data from multiple sources for analytics and operational use.
• Work with large datasets and ensure high data quality and availability.
• Develop and maintain ETL workflows using standard tools and scripting.
• Automate data extraction, transformation, and loading processes across systems.
• Monitor and optimize performance of data workflows for speed and efficiency.
• Develop, maintain, and optimize complex SQL queries, stored procedures, functions, and views.
• Design and implement relational database schemas and indexing strategies.
• Ensure data integrity, security, and compliance within SQL Server environments.
• Work with MongoDB for storing and querying unstructured or semi-structured data.
• Design document-based data models and manage performance tuning for MongoDB.
• Handle replication and backup strategies where applicable.
• Analyze complex data requirements and translate them into efficient technical solutions.
• Identify data-related issues, perform root-cause analysis, and deliver timely resolutions.
• Work closely with data analysts, software engineers, and business stakeholders to understand requirements.
• Participate in code reviews, team planning sessions, and cross-functional meetings.
• Take ownership of assigned tasks with accountability and attention to detail.
• Exhibit a proactive approach to delivering solutions and supporting team goals.
• Contribute to architectural discussions and recommend improvements based on industry best practices.

• Bachelor’s degree in Computer Science, Information Systems, or a related field.
• 2–3 years of experience in data engineering or database development roles.
• Strong proficiency in SQL Server (T-SQL, indexing, optimization).
• Hands-on experience with MongoDB or other NoSQL technologies.
• Familiarity with data pipeline tools and ETL development.
• Working knowledge of Python or similar scripting languages.
• Understanding of data modeling, normalization, and data warehousing concepts.
• Strong analytical thinking and problem-solving skills.
• Excellent communication and teamwork abilities.