{"id":8062,"date":"2025-10-25T13:35:24","date_gmt":"2025-10-25T17:35:24","guid":{"rendered":"https:\/\/datavizexplorer.org\/dir\/?page_id=8062"},"modified":"2025-12-15T00:44:26","modified_gmt":"2025-12-15T04:44:26","slug":"checklist-data-engineer","status":"publish","type":"page","link":"https:\/\/datavizexplorer.org\/dir\/checklist-data-engineer\/","title":{"rendered":"Free Exclusive Career Checklist: Beginner Data Engineer"},"content":{"rendered":"
\n

\ud83d\udd11 Free Exclusive Career Checklist:
\nBeginner Data Engineer<\/h2>\n

This checklist outlines the initial steps to build foundational skills<\/strong> and start your career in Data Engineering and Pipeline Development.<\/p>\n

\n

1. Core Programming & Database Skills<\/h3>\n\n\n\n\n\n\n\n\n\n
Step<\/th>\nAction Item<\/th>\nStatus<\/th>\n<\/tr>\n<\/thead>\n
1.1<\/td>\nMaster Advanced SQL:<\/strong> Become proficient in writing complex DDL, DML, and stored procedures for data warehousing (e.g., creating views, indexing).<\/td>\n<\/td>\n<\/tr>\n
1.2<\/td>\nDevelop Python Proficiency:<\/strong> Master Python for scripting, I\/O operations (file reading\/writing), and connecting to APIs to extract data.<\/td>\n<\/td>\n<\/tr>\n
1.3<\/td>\nUnderstand Data Modeling:<\/strong> Learn and apply concepts of Dimensional Modeling (Star and Snowflake schemas).<\/td>\n<\/td>\n<\/tr>\n
1.4<\/td>\nLearn Version Control (Git):<\/strong> Practice standard Git workflows (clone, branch, commit, push, merge) for collaborative code development.<\/td>\n<\/td>\n<\/tr>\n
1.5<\/td>\nBuild a Local Pipeline:<\/strong> Create a simple ETL pipeline using Python to extract data from a flat file, clean it, and load it into a local PostgreSQL or SQLite database. (Crucial)<\/strong><\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

2. Tooling & Cloud Exposure<\/h3>\n\n\n\n\n\n\n\n\n\n
Step<\/th>\nAction Item<\/th>\nStatus<\/th>\n<\/tr>\n<\/thead>\n
2.1<\/td>\nCloud Storage Setup:<\/strong> Create a free-tier account on AWS, GCP, or Azure and learn to upload\/manage data in object storage (S3, GCS, Blob Storage).<\/td>\n<\/td>\n<\/tr>\n
2.2<\/td>\nData Warehouse Basics:<\/strong> Run basic queries on a cloud data warehouse (e.g., Snowflake, BigQuery) to understand columnar storage and query costs.<\/td>\n<\/td>\n<\/tr>\n
2.3<\/td>\nOrchestration Concept:<\/strong> Understand the purpose of orchestrators like Airflow and list the key components (DAGs, tasks, scheduling).<\/td>\n<\/td>\n<\/tr>\n
2.4<\/td>\nContainers (Docker):<\/strong> Set up Docker and containerize your local Python ETL pipeline, making it reproducible.<\/td>\n<\/td>\n<\/tr>\n
2.5<\/td>\nData Quality\/Monitoring:<\/strong> Learn basic Data Quality concepts (freshness, completeness, validity) and implement simple checks within your pipeline script.<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

3. Portfolio & Career Kickoff<\/h3>\n\n\n\n\n\n\n\n\n\n
Step<\/th>\nAction Item<\/th>\nStatus<\/th>\n<\/tr>\n<\/thead>\n
3.1<\/td>\nCreate a GitHub Portfolio:<\/strong> Host your working pipeline code and data modeling documentation on GitHub, ensuring clean READMEs.<\/td>\n<\/td>\n<\/tr>\n
3.2<\/td>\nFocus on Pipeline Resilience:<\/strong> Modify your portfolio project to include basic error handling (try\/except blocks) and logging.<\/td>\n<\/td>\n<\/tr>\n
3.3<\/td>\nUpdate Resume Keywords:<\/strong> Use terms like ETL\/ELT, Dimensional Modeling, Cloud Storage, and **Python Scripting** to target entry-level roles.<\/td>\n<\/td>\n<\/tr>\n
3.4<\/td>\nConnect with Professionals:<\/strong> Identify 5-10 Data Engineers on LinkedIn and ask brief, respectful questions about their daily tech stack.<\/td>\n<\/td>\n<\/tr>\n
3.5<\/td>\nPrepare for SQL\/Python Screening:<\/strong> Practice solving 10-15 intermediate-level SQL and Python coding challenges common in first-round interviews.<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
Data Career Checklist Series<\/strong>\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 DataViz Explorer\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0Page 1 of 1\u00a0<\/span>\n<\/div>\n<\/div>\n
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\nDataViz Explorer<\/span> C.A.I.P.O Barbados Business Registration \u211687900\u00ae
\n<\/span><\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

\ud83d\udd11 Free Exclusive Career Checklist: Beginner Data Engineer This checklist outlines the initial steps to build foundational skills and start your career in Data Engineering and Pipeline Development. 1. Core Programming & Database Skills Step Action Item Status 1.1 Master Advanced SQL: Become proficient in writing complex DDL, DML, and stored procedures for data warehousing […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"yasr_overall_rating":0,"yasr_post_is_review":"","yasr_auto_insert_disabled":"","yasr_review_type":"","footnotes":""},"class_list":["post-8062","page","type-page","status-publish","hentry"],"yoast_head":"\nDataViz Explorer - Free Exclusive Career Checklist: Beginner Data Engineer<\/title>\n<meta name=\"description\" content=\"\ud83d\udd11 Free Exclusive Career Checklist: Beginner Data Engineer This checklist outlines the initial steps to build foundational skills and start your career in\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/datavizexplorer.org\/dir\/checklist-data-engineer\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"DataViz Explorer - 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