Data Engineer

We are seeking a highly skilled and detail-oriented Data Engineer to join our client. As a Data Engineer, you will design, construct, and maintain scalable data solutions to support data-driven decision-making throughout our organization. You'll work closely with cross-functional teams, including analysts, data scientists, and engineers, to ensure our data architecture is optimized for efficiency and performance.

• Data Pipeline Development: Design, develop, and manage robust, scalable, and efficient data pipelines to ingest, process, and store structured and unstructured data from multiple sources.
• Data Integration: Collaborate with stakeholders to integrate data from proprietary and third-party applications to create centralized datasets.
• Data Modeling: Develop and maintain comprehensive database designs, schemas, and data models to enable seamless querying and reporting.
• Performance Optimization: Continuously improve data pipeline performance, including processing speed, reliability, and scalability.
• Data Quality: Implement and utilize tools to ensure data accuracy, consistency, and integrity throughout the data lifecycle.
• Cloud Infrastructure: Set up and manage cloud-based data platforms (e.g., AWS, Azure, Google Cloud) and leverage cloud-native tools for storage and analytics.
• Collaboration: Work closely with data scientists and analysts to ensure data availability and align datasets with business objectives.
• Documentation: Create thorough documentation for all pipelines, schemas, and workflows to streamline team collaboration and ensure compliance.
• Bachelor's degree in Computer Science, Data Engineering, or a related field.
• Proven experience as a Data Engineer or in a similar role (2-4+ years preferred).
• Strong programming skills in languages such as Python, Java, or Scala.
• Proficiency in databases (e.g., MySQL, PostgreSQL, NoSQL) and data modeling.
• Experience with ETL/ELT tools (e.g., Apache Airflow, Talend, Informatica).
• Familiarity with cloud data platforms (e.g., AWS, Google Cloud Platform, Microsoft Azure).
• Knowledge of big data frameworks (e.g., Hadoop, Spark).
• Excellent problem-solving and analytical skills.