Responsibilities:

• Design, build, and manage scalable data pipelines and systems to support data integration and analysis.
• Collaborate with data scientists, analysts, and software engineers to ensure data accessibility and reliability.
• Develop, test, and maintain architectures such as databases, large-scale processing, and APIs.
• Implement processes and technologies for data acquisition and data transformation.
• Ensure data quality and consistency across various databases and systems.
• Identify, design, and implement internal process improvements, including optimizing data delivery and streamlining processes.
• Automate manual processes, optimize data delivery, and redesign infrastructure for greater scalability.
• Monitor and troubleshoot data pipeline issues in real-time.

Requirements:

• Proven experience (1-2 years) as a Data Engineer or in a similar role.
• Strong knowledge of SQL and experience with relational databases.
• Experience with big data tools such as Hadoop, Spark, Kafka, etc.
• Proficiency in data modeling, ETL development, and data warehousing.
• Familiarity with data pipeline and workflow management tools.
• Experience with programming languages (e.g., Python, Java, Scala).
• Knowledge of cloud platforms (AWS, Azure, GCP) and related services.
• Understanding of data privacy and security regulations.

Qualifications:

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
• Demonstrable knowledge of emerging technologies and willingness to learn new tools and technologies.
• Strong problem-solving skills and attention to detail.
• Excellent communication and teamwork skills.
• Ability to manage multiple tasks and deadlines.

Additional Considerations:

• Experience in a similar on-site work setting is preferred.
• Familiarity with machine learning algorithms is a plus.
• Certifications in data engineering or cloud technologies are an advantage.