Highly Skilled Data Engineer for Cloud and Data Systems

2 weeks ago

palakkad, India beBeeDataEngineering Full time

Job Title: Senior Data EngineerAbout the RoleWe are seeking a highly skilled Senior Data Engineer to design, develop, and optimize high-performance data pipelines and systems. The ideal candidate will have strong experience with cloud platforms, modern ETL/ELT tools, and deep technical skills in Python, SQL, and distributed data frameworks.Key ResponsibilitiesDesign, develop, and maintain scalable and reliable ETL/ELT pipelines to ensure seamless data flow.Build data models, data marts, and warehouses to support analytics and reporting needs, driving business insights and decision-making.Work with large-scale structured and unstructured datasets across multiple sources, ensuring data quality and integrity.Implement data quality, validation, and monitoring frameworks to detect and resolve issues promptly.Optimize existing pipelines for better performance, cost efficiency, and maintainability, minimizing downtime and improving overall system health.Collaborate with cross-functional teams, including Data Science, BI, Product, and Engineering, to gather and implement data requirements, fostering open communication and collaboration.Write optimized SQL queries and well-structured, maintainable Python code, adhering to industry standards and best practices.Support production pipelines by troubleshooting issues and performing root cause analysis, ensuring timely resolution and minimal disruption.Utilize version control, CI/CD, and automated deployment tools for data engineering tasks, ensuring consistency, reliability, and scalability.Ensure compliance with data security, privacy, and governance standards, protecting sensitive information and maintaining regulatory adherence.Requirements and Qualifications5+ years of hands-on experience in Data Engineering, with a proven track record of delivering high-quality solutions.Strong programming skills in Python and SQL, with expertise in ETL frameworks (Airflow, dbt, Spark, Glue, Dataflow, etc.).Experience with cloud data platforms (AWS, Azure, or GCP), leveraging their capabilities and features to drive innovation.Strong understanding of data modelling and data warehouse/lakehouse architectures, designing and implementing efficient and scalable solutions.Experience working with big data tools (Spark, Kafka, Hadoop) is a plus, enabling the ability to handle large-scale data processing and analysis.Experience with source control (Git) and CI/CD pipelines, ensuring version control, collaboration, and deployment efficiency.Good problem-solving skills and ability to work in cross-functional teams, fostering open communication and collaboration.Bonus RequirementsExperience with Snowflake, Redshift, BigQuery, Databricks, or Synapse, expanding skillset and versatility.Exposure to event-driven or real-time data streaming architectures, enabling the ability to process and analyze high-volume data streams.Experience integrating with ML pipelines or supporting Data Science workloads, driving innovation and collaboration.Familiarity with containerization (Docker, Kubernetes), streamlining deployment and management processes.

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