Key Responsibilities:

• Design, build, and maintain scalable and efficient big data pipelines for data ingestion, processing, and storage.
• Develop and optimize data architecture to handle large volumes of structured and unstructured data.
• Collaborate with data scientists, analysts, and engineers to ensure data quality and accessibility.
• Implement and manage big data technologies such as Hadoop, Spark, Kafka, and others.
• Automate data workflows and build reusable data processing frameworks.
• Monitor and troubleshoot data pipelines and system performance to ensure reliability and scalability.
• Ensure data security and compliance with relevant regulations (e.g., GDPR).
• Collaborate with cross-functional teams to align data solutions with business needs and goals.

Required Qualifications:

• Bachelor's degree in Computer Science, Data Engineering, or a related field.
• Experience working with big data technologies (e.g., Hadoop, Spark, Kafka).
• Proficiency in programming languages like Python, Java, or Scala.
• Strong knowledge of SQL and NoSQL databases.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with data warehousing and ETL processes.
• Knowledge of distributed systems and parallel computing.
• Strong problem-solving skills and ability to work in a fast-paced environment.

Preferred Skills:

• Experience with data lakes and data processing frameworks.
• Knowledge of real-time data streaming technologies.
• Familiarity with DevOps practices and containerization tools (e.g., Docker, Kubernetes).
• Experience with data governance and data security best practices.
• Excellent communication and teamwork skills.

Salary and Benefits:

• Competitive salary
• Health insurance and wellness programs.
• Paid vacation and public holidays.
• Opportunities for professional growth and career development.
• Collaborative and innovative work environment.