> Markdown version of [/jobs/ext/1021500-snowflake-data-engineer](https://www.wearedevelopers.com/jobs/ext/1021500-snowflake-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Snowflake Data Engineer - **Company:** PROLIM Global Corporation - **Location:** Plano, United States - **Contract:** Internship / Graduate position - **Skills:** Amazon Web Services, Microsoft Azure, Cloud Computing, Computer Programming, Databases, Information Engineering, Extract Transform Load (ETL), Data Structures, Data Warehousing, Database Queries, Dimensional Modeling, Python (Programming Language), Object-Oriented Software Development, Performance Tuning, Cloud Services, SQL Databases, Talend, Data Processing, Google Cloud, Data Ingestion, Azure Data Factory, Snowflake, Pyspark, AWS Glue, Data Pipelines - **Published:** June 9, 2026 - **Apply:** https://www.dice.com/job-detail/1d29495f-14f0-428d-a351-5ff8460edf1d ## About the Role 1. Snowflake Certification + Must possess at least one valid Snowflake certification (e.g., SnowPro Core or equivalent). + Candidate should be able to demonstrate understanding of Snowflake architecture, virtual warehouses, databases, schemas, stages, and data loading concepts. 2. SQL Proficiency + Strong understanding of SQL fundamentals. + Hands-on experience writing complex queries involving joins, subqueries, CTEs, window functions, aggregations, and performance optimization. + Ability to solve practical SQL-based scenarios during interviews. 3. Python / PySpark Skills + Good working knowledge of Python programming. + Familiarity with data processing using PySpark. + Understanding of data structures, functions, error handling, and basic object-oriented programming concepts. 4. Project Experience + Must have completed at least 1 2 academic, internship, personal, or training projects related to data engineering, analytics, or cloud data platforms. + Should be able to clearly explain: + Business use case + Architecture/design + Technologies used + Individual contribution * Challenges faced and solutions implemented Preferred (Good-to-Have) Skills 1. ETL/ELT Tool Exposure + Exposure to one or more ETL/ELT tools such as: + Fivetran + Hevo Data + Informatica + Talend + Azure Data Factory (ADF) + AWS Glue 2. Basic understanding of data ingestion and pipeline concepts. 3. Cloud & Data Warehousing Fundamentals + Basic understanding of cloud platforms (AWS, Azure, or Google Cloud Platform). + Familiarity with data warehousing concepts, dimensional modeling, and data pipelines. Behavioral & Problem-Solving Skills 1. Analytical and Problem-Solving Ability + Strong logical thinking and analytical mindset. + Ability to break down problems and propose practical solutions. + Comfortable working with data and troubleshooting issues. 1. Communication Skills + Good verbal and written communication skills. + Ability to explain technical concepts clearly and confidently. + Should be able to participate effectively in client-facing or team discussions. 2. Learning Attitude + Demonstrates eagerness to learn new technologies and adapt to changing project requirements. + Shows initiative in completing certifications, hands-on labs, and self-learning activities. ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How we built an AI-powered code reviewer in 80 hours](https://www.wearedevelopers.com/videos/1511-how-we-built-an-ai-powered-code-reviewer-in-80-hours) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Tips, Techniques, and Common Pitfalls Debugging Kafka](https://www.wearedevelopers.com/videos/838-tips-techniques-and-common-pitfalls-debugging-kafka) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Why Upskilling And Reskilling is Important For Developers](https://www.wearedevelopers.com/magazine/428-why-upskilling-and-reskilling-is-important-for-developers) - [Should senior developers refuse interview coding challenges?](https://www.wearedevelopers.com/magazine/29-should-senior-developers-refuse-interview-coding-challenges)