𝑀𝑦 𝑗𝑜𝑢𝑟𝑛𝑒𝑦 𝑖𝑛𝑡𝑜 𝑑𝑎𝑡𝑎 𝑒𝑛𝑔𝑖𝑛𝑒𝑒𝑟𝑖𝑛𝑔 𝑏𝑒𝑔𝑎𝑛 𝑤𝑖𝑡ℎ 𝑎 𝑠𝑖𝑚𝑝𝑙𝑒 𝑐𝑢𝑟𝑖𝑜𝑠𝑖𝑡𝑦 - ℎ𝑜𝑤 𝑑𝑜𝑒𝑠 𝑟𝑎𝑤 𝑑𝑎𝑡𝑎 𝑡𝑟𝑎𝑛𝑠𝑓𝑜𝑟𝑚 𝑖𝑛𝑡𝑜 𝑚𝑒𝑎𝑛𝑖𝑛𝑔𝑓𝑢𝑙 𝑖𝑛𝑠𝑖𝑔ℎ𝑡𝑠? 𝑂𝑣𝑒𝑟 𝑡𝑖𝑚𝑒, 𝑡ℎ𝑖𝑠 𝑐𝑢𝑟𝑖𝑜𝑠𝑖𝑡𝑦 𝑒𝑣𝑜𝑙𝑣𝑒𝑑 𝑖𝑛𝑡𝑜 𝑎 𝑝𝑎𝑠𝑠𝑖𝑜𝑛 𝑓𝑜𝑟 𝑏𝑢𝑖𝑙𝑑𝑖𝑛𝑔 𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑡 𝑑𝑎𝑡𝑎 𝑠𝑦𝑠𝑡𝑒𝑚𝑠 & 𝑡𝑎𝑐𝑘𝑙𝑖𝑛𝑔 𝑐𝑜𝑚𝑝𝑙𝑒𝑥 𝑑𝑎𝑡𝑎 𝑝𝑖𝑝𝑒𝑙𝑖𝑛𝑒 𝑐ℎ𝑎𝑙𝑙𝑒𝑛𝑔𝑒𝑠.
🧠 KNOWLEDGE (K).
- Strong foundation in data engineering principles (ETL pipelines, DB management, workflow orchestration, data modeling & schema design).
- Knowledge of data storytelling & selecting chart models to effectively present insights.
- Quantitative & qualitative data analysis expertise, applying descriptive, diagnostic & predictive analysis techniques for insights.
🛠 SKILLS (S).
- Programming Languages. Python (3+ years), Bash.
- Relational Databases. MS SQL Server, MySQL, PostgreSQL (for querying, optimizing, and managing - 2+ years)
- Big Data & Orchestration. PySpark (distributed data processing - 1+ year), Airflow (workflow automation), Kafka (real-time data streaming - 1+ year)
⚡ ABILITIES (A).
- Assist in designing & implementing scalable data pipelines under mentorship.
- Support in debugging and troubleshooting data workflows to ensure efficiency and reliability.
📌 OTHER ATTRIBUTES (O). Problem-solving, teamwork, adaptability, attention to detail, specialization & generalization.
I am passionate about 𝘀𝗵𝗮𝗿𝗶𝗻𝗴 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 & documenting my learning journey in the data field. I enjoy writing to help others navigate 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 & 𝗰𝗮𝗿𝗲𝗲𝗿 𝗴𝗿𝗼𝘄𝘁𝗵.
Featured Works in LinkedIn.
- Online Assessment HackerRank Report – Database Questions For Data Engineer(ing). A PostgreSQL-focused guide with step-by-step solutions for HackerRank DB assessments.
- Preparation For Applying Jobs. Insights into the hiring pipeline for developers, from writing CV to negotiating an offer.
- Data Engineer Roadmap. A structured Notion guide on what to learn to build a career in DE.
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