High-Performance Data Specialist

5 days ago

rajahmundry, India beBeeDataEngineer Full time

Senior Data Engineer Job DescriptionWe are seeking a highly skilled Senior Data Engineer to join our team. As a key member of our data engineering team, you will be responsible for designing, building, and optimizing 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 Responsibilities:Design and Develop Scalable ETL Pipelines: Design, develop, and maintain scalable and reliable ETL pipelines that integrate multiple data sources.Build Data Models and Warehouses: Build robust data models, data marts, and data warehouses to support analytics and reporting needs.Work with Large-Scale Datasets: Work with large-scale structured and unstructured datasets across multiple sources, ensuring efficient processing and storage.Implement Data Quality Frameworks: Implement data quality, validation, and monitoring frameworks to ensure data accuracy and consistency.Optimize Existing Pipelines: Optimize existing pipelines for better performance, cost efficiency, and maintainability.Collaborate with Cross-Functional Teams: Collaborate with Data Science, BI, Product, and Engineering teams to gather and implement data requirements.Write Optimized Code: Write optimized SQL queries and well-structured, maintainable Python code.Troubleshoot Issues: Troubleshoot issues and perform root cause analysis to ensure smooth operation of production pipelines.Required Skills & Experience:5+ Years of Experience: 5+ years of hands-on experience in Data Engineering, with a strong focus on cloud platforms, ETL frameworks, and distributed data frameworks.Programming Skills: Strong programming skills in Python and SQL, with expertise in data modeling and data warehouse architectures.ETL Frameworks: Experience with ETL frameworks such as Airflow, dbt, Spark, Glue, Dataflow, etc.Cloud Platforms: Expertise in cloud data platforms, including AWS, Azure, or GCP.Big Data Tools: Experience working with big data tools such as Spark, Kafka, Hadoop, etc.Source Control: Experience with source control, including Git, and CI/CD pipelines.Preferred / Nice-to-Have Skills:Additional Cloud Platforms: Experience with additional cloud platforms such as Snowflake, Redshift, BigQuery, Databricks, or Synapse.Event-Driven Architectures: Exposure to event-driven or real-time data streaming architectures.ML Pipelines: Experience integrating with ML pipelines or supporting Data Science workloads.Containerization: Familiarity with containerization, including Docker and Kubernetes.

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