Data Engineer

Job Type: Contract
Experience Level: 3+ YearsJob Overview:We are seeking an experienced Data Engineer to join our dynamic team. As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines, processing large-scale datasets, and ensuring data availability for analytics. The ideal candidate will have a strong background in distributed systems, database design, and data engineering practices, with hands-on experience working with modern data technologies.Key Responsibilities:Design, implement, and optimize data pipelines using tools like Spark, Kafka, and Airflow to handle large-scale data processing and ETL tasks.Work with various data storage systems (e.g., PostgreSQL, MySQL, NoSQL databases) to ensure efficient and reliable data storage and retrieval.Collaborate with data scientists, analysts, and other stakeholders to design solutions that meet business needs and data requirements.Develop and maintain robust, scalable, and efficient data architectures and data warehousing solutions.Process structured and unstructured data from diverse sources, ensuring data is cleansed, transformed, and loaded effectively.Optimize query performance and troubleshoot database issues to ensure high data availability and minimal downtime.Implement data governance practices to ensure data integrity, security, and compliance.Participate in code reviews, knowledge sharing, and continuous improvement of team processes.Required Skills & Experience:Minimum of 3+ years of relevant hands-on experience in data engineering.Extensive experience with distributed systems (e.g., Apache Spark, Apache Kafka) for large-scale data processing.Proficiency in SQL and experience working with relational databases like PostgreSQL, MySQL, and NoSQL technologies.Strong understanding of data warehousing concepts, ETL processes, and data pipeline design.Experience building and managing data pipelines using Apache Airflow or similar orchestration tools.Hands-on experience in data modeling, schema design, and optimizing database performance.Solid understanding of cloud-based data solutions (e.g., AWS, GCP, Azure) and familiarity with cloud-native data tools is a plus.Ability to work collaboratively with cross-functional teams and communicate complex technical concepts to non-technical stakeholders.Preferred Skills:Experience with containerization and orchestration tools such as Docker and Kubernetes.Familiarity with data lakes, data mesh, or data fabric architectures.Knowledge of machine learning pipelines or frameworks is a plus.Experience with CI/CD pipelines for data engineering workflows.Education:Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.Mode of Work: 3 days work from office/2 days work from home.