Data Engineer

Roles and Responsibilities :

Data Pipeline Development: Design and develop scalable data pipelines to process and transform large volumes of structured and unstructured data.

 Data Processing: Build and optimize data processing frameworks using Apache Spark.

 Data Integration: Integrate data from multiple sources to create reliable and efficient data workflows. Data Management: Ensure efficient storage, retrieval, and transformation of data for analytics and reporting.

System Performance: Monitor and optimize data pipelines for performance, scalability, and reliability. Troubleshooting: Identify and resolve issues in data pipelines and processing systems to ensure data accuracy and availability.

 Collaboration: Work closely with data scientists, backend engineers, and product teams to understand data requirements and deliver solutions.

 Documentation: Maintain clear documentation of data pipelines, data models, and workflows. Continuous Improvement: Stay updated with emerging technologies and best practices in big data and data engineering.

Job Requirements :

Required Skills Experience: 1–3 years of hands-on experience in data engineering or backend development.

 Programming Languages: Strong experience with Java/Python  and Scala.

Big Data Frameworks: Hands-on experience with Apache Spark for data processing and analytics.

 Data Processing: Understanding of distributed data processing concepts and large-scale data handling.

 Problem-Solving Skills: Strong analytical and troubleshooting abilities.

 Ownership: High sense of responsibility and accountability for deliverables.

 Communication: Good verbal and written communication skills.

Team Player: Ability to work effectively in a collaborative team environment