Responsibilities:

• Design, develop, and maintain robust and scalable ETL/ELT pipelines to ingest and transform large datasets from various sources.
• Optimize and manage databases (SQL/NoSQL) to ensure efficient data storage, retrieval, and manipulation for both structured and unstructured data.
• Collaborate with data scientists, analysts, and engineers to integrate data from disparate sources and ensure smooth data flow between systems.
• Implement and maintain data validation and monitoring processes to ensure data accuracy, consistency, and availability.
• Automate repetitive data engineering tasks and optimize data workflows for performance and scalability.
• Work closely with cross-functional teams to understand their data needs and provide solutions that help scale operations.
• Ensure proper documentation of data engineering processes, workflows, and infrastructure for easy maintenance and scalability

Desired Profile:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• 5+ years of hands-on experience as a Data Engineer or in a related data-driven role.
• Strong experience with ETL tools like Apache Airflow, Talend, or Informatica.
• Expertise in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra).
• Strong proficiency in Python, Scala, or Java for data manipulation and pipeline development.
• Experience with cloud-based platforms (AWS, Google Cloud, Azure) and their data services (e.g., S3, Redshift, BigQuery).
• Familiarity with big data processing frameworks such as Hadoop, Spark, or Flink.
• Experience in data warehousing concepts and building data models (e.g., Snowflake, Redshift).
• Understanding of data governance, data security best practices, and data privacy regulations (e.g., GDPR, HIPAA).
• Familiarity with version control systems like Git.