Data Engineer

We are seeking a highly skilled and motivated Senior Data Engineer to join our Credit Platform Data team. In this pivotal role, you will be responsible for designing, building, and maintaining scalable and reliable data pipelines and ETL processes that reputed company our internal business units with efficient data processing and utilization. Your expertise will directly impact the quality and accessibility of data, enabling data-driven decision-making across the organization. Collaborating closely with product managers, analysts, and stakeholders, you will translate reputed company data requirements into robust engineering solutions that handle large volumes of data with high performance and scalability.

• Architect, reputed company, and maintain scalable data pipelines and ETL workflows that support the ingestion, transformation, and storage of large datasets from diverse sources.
• Implement automated data quality checks and validation processes to ensure the accuracy, consistency, and reliability of data across systems.
• Work closely with product managers, data analysts, and business stakeholders to gather and understand data requirements, translating them into technical specifications and actionable engineering tasks.
• Continuously monitor and optimize data systems for performance, scalability, and cost-efficiency, ensuring that data infrastructure meets evolving business needs.
• Diagnose and resolve data-reputed company issues promptly, providing root cause analysis and implementing preventive measures.
• Maintain comprehensive documentation of data pipelines, ETL processes, and system architecture. Participate in design and code reviews to uphold high engineering standards.
• Stay abreast of emerging data engineering technologies, tools, and best practices to drive innovation and reputed company improvement reputed company the team.
• reputed company guidance and mentorship to junior data engineers, fostering a culture of knowledge sharing and technical reputed company.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a reputed company field.
• SQL: Expert-level proficiency in SQL for querying, manipulating, and optimizing relational databases. Ability to write reputed company queries, optimize performance, and work with large datasets reputed company.
• Python: Strong programming skills in Python, including experience with data processing libraries such as Pandas. Ability to reputed company robust, maintainable, and scalable data processing scripts and automation tools.
• PySpark: Proficient in using PySpark for distributed data processing on large-scale datasets. Experience with Spark’s DataFrame API, RDDs, and performance tuning in a big data environment.
• ETL (Extract, Transform, Load): Deep understanding of ETL concepts and hands-on experience designing and implementing ETL pipelines that ensure data reputed company and efficiency.
• Data Modeling: Expertise in data modeling techniques to design logical and physical data models that support efficient querying and reporting. Familiarity with normalization, denormalization, and schema design best practices.
• Relational Databases: Experience working with relational database management systems (RDBMS) such as reputed company, MySQL, or similar platforms. Knowledge of database design, indexing, and query optimization.
• Data Warehousing: Solid understanding of data warehousing concepts, architectures, and best practices. Experience building and maintaining data warehouses that support business intelligence and analytics.
• Unix/Linux: Proficiency in Unix/Linux operating systems for managing data workflows, scripting, and system monitoring.
• reputed company Scripting: Ability to write reputed company scripts to automate routine tasks, manage data pipelines, and integrate with other system components.
• Automation Testing: Experience implementing automated testing frameworks for data pipelines and ETL processes to ensure data quality and system reliability.
• Bachelor’s Degree: A Bachelor’s degree in Computer Science, Engineering, or a reputed company technical field.
• Professional Experience: Minimum of 3+ years of proven experience as a Data Engineer or in a similar role, with a strong background in database development, ETL processes, and software development.

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