Data Engineer

Description

• Data Architecture Design: - Collabo rate with stakeholders to understand data requirements and design scalable data architectures. - Develop and maintain data models, schemas, and structures that align with business objectives. • Data Pipeline Development: - Design, build, and optimize data pipelines for the extraction, transformation, and loading (ETL) of data from diverse sources into centralized repositories. - Implement data integration processes to ensure data consistency and accuracy. • Database Management: - Administer and optimize databases to ensure high performance, security, and reliability. - Implement data partitioning, indexing, and other optimization techniques. • Data Quality Assurance: - Develop and implement data quality checks and validation processes to ensure the integrity of the data. - Troubleshoot and resolve data quality issues in collaboration with relevant teams. • Big Data Technologies: - Work with big data technologies such as Hadoop, Spark, and related ecosystems for large-scale data processing and analytics. • Collaboration and Communication: - Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements and deliver effective solutions. - Communicate complex technical concepts to non-technical stakeholders. • Automation and Scalability: - Implement automation scripts and tools to streamline data workflows and enhance system scalability. - Stay current with industry trends and technologies to continuously improve data engineering processes. • Security and Compliance: - Implement and adhere to data security and compliance standards, ensuring the protection of sensitive information. • Project Management: - Follow up and study project issues and block point. - Support and coordinate related stakeholders to ensure project deliverables are meet the deadline. • Bachelor’s Degree in Computer Science, Software Engineering, or a related field (or equivalent experience). • Proven experience as a Data Engineer or similar role, with a strong portfolio of data morphing and algorithm. • Strong understanding of back-end development using server-side languages (e.g., Java, PHP, Node.js, Python, Ruby) and frameworks (e.g., Spring boot, Laravel, Express, Django, Ruby on Rails). • Experience with database management systems (e.g., MySQL, MongoDB, PostgreSQL) and ability to write efficient SQL queries and SQL programming. • Experience with big data process framing such as apache Hadoop, apache Spark. • Experience with data warehouse concept and platform such as amazon redshift, google bigQuery or SnowFlake. • Experience with ETL concept and tool such as apache NIFI, apache AirFlow or Talend.. • Familiarity with version control systems (e.g., Git) and collaborative development workflows. • Familiarity with cloud platforms (e.g., AWS, Azure) and deploying applications in a cloud environment. • Excellent problem-solving skills and ability to troubleshoot and debug complex applications. • Strong communication and collaboration skills, with the ability to work effectively in a team environment.

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