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Remote flexibility, popular mid-level data engineer title, metro location, and broad skill requirements increase competition.
Data engineering skills (Python, ETL, SQL, cloud) are highly transferable across industries.
Explicit 3–5+ years, mandatory Python/ETL/SQL/AWS skills create strict shortlisting filters.
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Design, develop, and maintain high-performance Python applications and scalable data pipelines, including ETL processes.
Implement and integrate APIs, web scraping, and databases to extract and process data from diverse sources.
Ensure code quality, performance, and scalability; collaborate with cross-functional teams to deliver robust data solutions.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
3–5+ years of hands-on experience as a Data Engineer using Python.
Proficiency in Python libraries (Pandas, NumPy, Scrapy) and experience with SQL and relational databases.
Experience with data visualization tools (Power BI, Tableau) and cloud platforms such as AWS.
Experienced in developing and optimizing ETL pipelines and data processing algorithms with Python.
Able to work effectively in collaborative environments with cross-functional teams.
Demonstrates strong analytical skills and keeps updated with the latest advancements in Python and data engineering.