Design, develop, and implement scalable and efficient data pipelines using various tools and technologies (e.g., Python, SQL, Spark, Hadoop, Kafka, Airflow)
Extract, transform, and load (ETL) data from various sources (e.g., databases, APIs, files) into our data warehouse or data lake
Develop and maintain data quality and governance frameworks to ensure data accuracy and integrity
Collaborate with data analysts, scientists, and business stakeholders to understand their data needs and translate them into technical requirements
Optimize data pipelines for performance and cost-efficiency
Troubleshoot and resolve data-related issues
Stay updated on the latest data engineering trends and technologies
Qualification:
Bachelor’s degree in Computer Science, Engineering, or a related field
2+ years of experience as a Data Engineer or a similar role
Strong proficiency in Python and SQL
Experience with data warehousing and data lake technologies (e.g., Snowflake, AWS Redshift, Databricks)
Knowledge of ETL tools and frameworks (e.g., Talend, Informatica)
Experience with cloud platforms (e.g., AWS, GCP, Azure) is a plus
Excellent problem-solving and analytical skills
Ability to work independently and as part of a team
