Hiring For Data Engineer

Must-Have Skills

• Over 4 years of experience as a Data Engineer with proficiency in Python, R, SQL, and Excel (including data cleaning functions, filters, and pivot tables).
• Ability to perform data validation and ensure data consistency (identifying duplicates, missing values, outliers, and inconsistencies).
• Experience in data transformation, reshaping, aggregating, and normalizing data to prepare it for analysis
• Knowledge of missing data handling, including imputation techniques or strategies for dealing with incomplete datasets
• Summarizing or grouping data for analysis, ensuring consistency across multiple sources
• Strong understanding of data integrity and maintaining accurate and consistent data over time.
• Experience with data profiling, identifying patterns, anomalies, and key characteristics in datasets.
• Expertise in error detection, spotting and correcting outliers, misclassifications, and missing values.
• The ability to identify small inconsistencies and issues within large datasets.
• Strong problem-solving skills for resolving data issues and proposing solutions.
• Critical thinking for in-depth data analysis and understanding its implications.
• Excellent communication skills, with the ability to explain data issues and cleaning steps to non-technical stakeholders.
• Proficiency in handling structured data (tables, databases).
• Ability to clean data from various data sources (spreadsheets, databases, APIs, logs, etc.).
• Familiarity with working with common data file formats like CSV, XML, and Excel.

Good-to-Have Skills

• Basic understanding of statistics to identify anomalies, outliers, or trends in data.
• Experience in data visualization, using tools like Power BI or similar to identify trends and patterns.
• Experience in automating repetitive data cleaning tasks using scripts or workflow automation tools.
• Ability to handle batch processing, particularly when working with large datasets.