Chief Data Architecture Specialist

9 hours ago

Malappuram, India beBeeDataEngineer Full time

Job DescriptionWe are seeking a Senior Data Engineer to design, build, and optimize high-performance data pipelines and data 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 scalable and reliable ETL/ELT pipelines that meet the needs of our business.Build data models, data marts, and data warehouses to support analytics and reporting needs.Work with large-scale structured and unstructured datasets across multiple sources.Implement data quality, validation, and monitoring frameworks to ensure data integrity.Optimize existing pipelines for better performance, cost efficiency, and maintainability.Collaborate with cross-functional teams to gather and implement data requirements.Required Skills & Experience:The ideal candidate will have 5+ years of hands-on experience in Data Engineering. Strong programming skills in Python and SQL are required. Experience with ETL frameworks (Airflow, dbt, Spark, Glue, Dataflow, etc.) is also necessary. In addition, expertise in cloud data platforms (AWS, Azure, or GCP) and strong understanding of data modelling and data warehouse/lakehouse architectures are required.Benefits:As a Senior Data Engineer, you will have opportunities for professional growth and development in a dynamic and innovative environment. You will work closely with talented engineers and scientists to design, build, and deploy cutting-edge data systems and solutions. You will also have the opportunity to collaborate with other teams and stakeholders to identify and solve complex problems.Preferred Skills:While not required, experience with Snowflake, Redshift, BigQuery, Databricks, or Synapse, as well as familiarity with containerization (Docker, Kubernetes), is a plus. Additionally, exposure to event-driven or real-time data streaming architectures, and experience integrating with ML pipelines or supporting Data Science workloads is highly desirable.

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