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About the role
Data Engineering Intern : What You Will Do ● Build and maintain ELT pipelines using dbt, Fivetran, and Apache Airflow under senior guidance. ● Write clean, optimised SQL and Python for data transformation and ingestion tasks. ● Assist with Snowflake and Databricks platform work — schema design, warehouse configuration, cluster tuning. ● Run cost-analysis queries to identify over-spending patterns (auto-scaling, unpartitioned scans, idle clusters). ● Support data migration projects moving clients from legacy warehouses (SQL Server, Teradata, on-prem) to the cloud. ● Participate in code reviews, documentation, and knowledge-sharing within the engineering team. ● Contribute to internal tooling and reusable pipeline templates that accelerate client delivery. What We Are Looking For Must-have ● Bachelor's degree in Computer Science, Information Systems, or a related technical field (2025 or 2026 graduate). ● Strong SQL fundamentals — joins, aggregations, window functions, query optimisation basics. ● Python proficiency: writing scripts, working with pandas / PySpark, reading and writing to APIs or files. ● Understanding of data warehouse concepts — schemas, fact/dimension tables, partitioning, indexing. ● Genuine curiosity about data infrastructure and cloud platforms. Nice-to-have ● Hands-on exposure to Snowflake or Databricks through coursework, self-study, or internships. ● Familiarity with dbt (data build tool) — even working through the dbt Learn tutorials counts. ● Experience with any cloud provider (AWS, Azure, or GCP) at the student-project or certification level. ● Knowledge of orchestration tools such as Apache Airflow or Prefect
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