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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and maintain scalable ETL/ELT data pipelines ensuring reliability, performance, and data quality.
Build and optimize workflows for data ingestion and transformation from multiple sources to support analytics, ML, and AI initiatives.
Troubleshoot pipeline issues, implement monitoring and testing, and document data architecture and processes.
Minimum Requirements
2–5 years of relevant Data Engineering experience with production-grade data pipelines.
Strong proficiency in SQL and programming skills in Python or a similar language.
Hands-on experience with ETL/ELT pipelines, data warehousing, and data modeling.
Bachelor’s or Master’s degree in Computer Science, IT, Engineering, Data Science, or related field.
Ideal Candidate Profile
Experienced in managing end-to-end data pipeline reliability, performance, and scalability in a production environment.
Proficient in working with both structured and unstructured data using SQL, Python, and big data technologies such as Spark.
Familiar with cloud data platforms and modern data engineering tools (e.g., Airflow, Kafka, cloud warehouses) facilitating complex data workflows and governance.
