Key Responsibilities:

Design, develop, and maintain scalable data pipelines to process large volumes of data in real-time
Collaborate with cross-functional teams to identify and gather data requirements for business use cases
Build and maintain data warehousing solutions to support reporting and analytics needs
Ensure the availability and integrity of data through data quality assurance and data governance processes
Develop and implement data security and privacy measures to safeguard sensitive information
Optimize data infrastructure for performance, scalability, and cost efficiency
Conduct data analysis and provide insights to inform business decisions
Research and evaluate new technologies and techniques to enhance our data capabilities
Mentor and lead a team of data engineers, providing guidance on best practices and ensuring high-quality deliverables
Communicate complex technical concepts and solutions to non-technical stakeholders

Qualifications:

Bachelor's or Master's degree in Computer Science, Data Science, or a related field
Minimum of years of experience in data engineering, with at least years in a leadership or senior role
Strong experience with data warehousing, ETL processes, and data modeling
Proficiency in SQL and scripting languages such as Python or Java
Experience with cloud-based data platforms, preferably AWS or Azure
Familiarity with big data technologies such as Hadoop, Spark, or Kafka
Excellent problem-solving and analytical skills
Strong communication and collaboration skills
Proven experience in leading and mentoring a team
Ability to thrive in a fast-paced, dynamic environment

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