To transit from the DBA database role to data engineering

📌 𝐒𝐭𝐮𝐝𝐲 𝐃𝐚𝐭𝐚 𝐒𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞𝐬 𝐚𝐧𝐝 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬: Refresh your knowledge of essential data structures like arrays, linked lists, queues, stacks, trees, and graphs. Understand their properties, operations, and standard algorithms associated with them. You can refer to #crackingthecodinginterview book ✍

📌 𝐌𝐚𝐬𝐭𝐞𝐫 𝐓𝐢𝐦𝐞 𝐂𝐨𝐦𝐩𝐥𝐞𝐱𝐢𝐭𝐲 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: Practice analyzing the time complexity of algorithms. Understand concepts like Big O notation, best-case, worst-case, and average-case complexity. Be able to identify the most efficient algorithm for a given problem.

📌 𝐒𝐨𝐥𝐯𝐞 𝐂𝐨𝐝𝐢𝐧𝐠 𝐏𝐫𝐨𝐛𝐥𝐞𝐦𝐬: Practice solving coding problems commonly asked in data engineering interviews. Start with easier problems and gradually progress to more challenging ones.

📌 𝐑𝐞𝐯𝐢𝐞𝐰 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐂𝐨𝐧𝐜𝐞𝐩𝐭𝐬: Brush up on your knowledge of database concepts, including SQL queries, normalization, indexing, and data modeling. Understand the differences between various types of databases, such as relational, NoSQL, and columnar databases.

📌 𝐅𝐨𝐜𝐮𝐬 𝐨𝐧 𝐒𝐩𝐚𝐫𝐤 & 𝐇𝐚𝐝𝐨𝐨𝐩 𝐂𝐨𝐧𝐜𝐞𝐩𝐭𝐬: Stay informed about popular data engineering tools and technologies, such as Apache Spark, Hadoop, Apache Kafka, SQL databases, cloud platforms (AWS, GCP, Azure), and data warehousing solutions.

📌 𝐃𝐚𝐭𝐚 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠 𝐚𝐧𝐝 𝐄𝐓𝐋 𝐂𝐨𝐧𝐜𝐞𝐩𝐭𝐬: Familiarize yourself with data processing techniques and ETL (Extract, Transform, Load) workflows. Understand concepts like data ingestion, transformation, quality, and integration.

📌 𝐌𝐨𝐜𝐤 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰𝐬 𝐚𝐧𝐝 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞: Conduct mock interviews with friends or join coding interview practice groups. Practice articulating your thoughts and explaining your problem-solving approach. Get feedback and improve your interview skills.

In case you need help with mock interviews or creating a resume or need guidance with projects, feel free to book 1:1 LTM mentorship with me at Preplaced.