Data Engineer

Job Summary:

Key Responsibilities:

Design and implement efficient data cleansing routines to remove duplicates, correct anomalies, and validate data integrity.
Write robust Python scripts to automate data processing, transformation, and integration tasks.
Develop and optimize SQL queries for data extraction, aggregation, and reporting.
Work closely with data analysts, business stakeholders, and engineering teams to understand data requirements and deliver clean, structured datasets.
Build and maintain data pipelines that support large-scale data processing.
Monitor data workflows and troubleshoot issues to ensure accuracy and reliability.
Contribute to documentation of data sources, transformations, and cleansing logic.

Requirements:

Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field.
3+ years of hands-on experience in data engineering, with a focus on data quality and cleansing.
Strong proficiency in Python, including libraries like Pandas and NumPy.
Expert-level knowledge of SQL and working with relational databases (e.g., PostgreSQL, MySQL, SQL Server).
Familiarity with data profiling tools and techniques.
Excellent problem-solving skills and attention to detail.
Good communication and documentation skills.

Preferred Qualifications:

Experience with cloud platforms (AWS, Azure, GCP) and data services (e.g., S3, BigQuery, Redshift).
Knowledge of ETL tools like Apache Airflow, Talend, or similar.
Exposure to data governance and data cataloging practices.