Data Engineer

AI overview

Design and optimize ETL pipelines while collaborating with cross-functional teams to ensure data quality and support data analysis needs.

Design, develop, and optimize ETL pipelines to extract data from various sources, transform it into usable formats, and load it into our data warehouse.
Collaborate with cross-functional teams to understand data requirements and implement solutions that meet business needs.
Ensure data quality, integrity, and consistency by implementing best practices in data validation, cleansing, and transformation.
Monitor and troubleshoot ETL processes to ensure data is accurate, timely, and reliable.
Develop and maintain documentation for ETL processes, data flows, and data models.
Identify opportunities to improve existing ETL processes and implement enhancements for scalability and performance.
Work with data analysts and data scientists to provide them with the necessary data for reporting and analysis.

Bachelor’s degree in Computer Science, Information Technology, or a related field.
Min. 5 years of experience in Data Engineering field
Proven experience as a Data Engineer or in a similar role, with a focus on ETL processes.
Strong proficiency in SQL and experience with relational databases (e.g., MySQL, PostgreSQL).
Experience with ETL tools and technologies (e.g., Apache Airflow, Talend, Informatica).
Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and data warehousing solutions (e.g., Redshift, BigQuery, Snowflake).
Proficiency in programming languages such as Python or Java.
Excellent problem-solving skills and attention to detail.
Strong communication and collaboration skills.