Senior Data Engineer

2 weeks ago


India SAPBOT Technologies Full time

Senior Data Engineer (Sr. Developer) - Proficient in Azure Databricks, Azure Data Factory and Azure SQL DB - Proficient in designing and developing ingestion pipelines with DLT and Structured Streaming - Proficient in Databricks/Spark internals - Proficient in Spark jobs optimization techniques - Proficient in designing the pipelines with latest Databrick/Spark optimization techniques - Proficient in PySpark, SQL and Python for data engineering - Experience in developing and maintaining meta data driven data ingestion framework - Extensive experience in the data warehousing concepts - Certification in professional data bricks is preferred - Exhibits leadership skills The Senior Data Engineer will be responsible for building and maintaining robust, scalable, and efficient data pipelines that support our data-driven initiatives. You will work alongside data scientists, analysts, and other engineering teams to design, develop, and optimize data processing and transformation workflows. As a Senior Data Engineer, you will also ensure the reliability, performance, and scalability of data architectures while mentoring junior engineers and contributing to the development of best practices. Key Responsibilities : - Develop end-to-end data pipelines to ingest, transform, and store large-scale datasets using technologies like Azure Data Factory, Databricks, and SQL. - Work closely with data engineers, analysts, and business stakeholders to understand data needs and deliver solutions that support data-driven decision-making. - Develop data ingestion pipelines utilizing Delta Live Tables (DLT) and Structured - Streaming to handle both batch and real-time data ingestion requirements. - Continuously optimize the performance and scalability of data pipelines, ensuring data is processed efficiently and in a timely manner. - Implement processes to ensure the integrity, accuracy, and consistency of data, including monitoring and resolving data quality issues. - Troubleshoot and resolve data pipeline issues, set up monitoring systems, and proactively address performance or data-related problems. - Document data engineering processes, workflows, and standards. - Contribute to the development and adoption of best practices within the team. - Keep abreast of the latest data engineering technologies, methodologies, and trends to continuously improve and refine data engineering : - Bachelor's degree in Computer Science, Data Engineering, Information Technology, or a related field. - 5 years of experience in data engineering, building and managing data pipelines, and working with large datasets. - Proficiency in working with Azure Data Factory, Databricks, and SQL-based data solutions. - Strong experience in data pipeline development, data processing, and transformation using Spark Structured Streaming and Delta Live Tables. - Familiarity with cloud-based data storage solutions (e.g., Azure Blob Storage, Azure SQL DB, or similar platforms). - Solid understanding of ETL/ELT processes and data warehousing concepts. - Azure Data Engineer, or related certifications, are preferred but not mandatory. - Strong programming skills in Python, SQL, and other relevant data engineering languages. - Experience with data orchestration tools like Apache Airflow or Azure Data Factory. - Proficiency in using version control systems (e.g., Git) and CI/CD pipelines for data solutions. - Strong analytical skills, with the ability to troubleshoot complex data issues and optimize performance across data systems. - Excellent teamwork and communication skills, with the ability to work with cross- - functional teams and communicate complex technical concepts to non-technical stakeholders. (ref:hirist.tech)



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