Name of the position: Data Engineer
No. of resources needed : 01
Mode: Contract (2 Months with Possible Extension)
Years of experience: 3+ Years
Job Summary:
We are looking for a highly motivated and detail-oriented Data Engineer with a strong background in data cleansing, Python scripting, and SQL to join our team. The ideal candidate will play a critical role in ensuring data quality, transforming raw datasets into actionable insights, and supporting data-driven decision-making across the organization.
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.