Team Leadership and Management: 

Lead and oversee a medium team, ensuring their professional development, motivation, and high performance. 

Provide coaching, guidance, and technical expertise to team members, promoting a culture of continuous learning and growth. 

Establish clear goals and expectations, monitor progress, and provide regular feedback to team members. 

Aligning Business Needs with Data Platforms: 

Collaborate closely with business stakeholders and data scientists to understand their requirements and translate them into scalable data solutions. 

Design and implement data solutions that effectively address business needs while ensuring data quality, accuracy, and security. 

Identify opportunities to streamline and automate data management processes, ensuring efficient utilization of resources. 

Act as a liaison between the data engineering team and senior management, communicating progress, challenges, and recommendations. 

Collaborate with stakeholders to create and maintain a roadmap for data engineering initiatives, aligning with the overall business strategy. 

Present complex technical concepts and solutions in a clear and concise manner to both technical and non-technical audiences. 

Technical Leadership and Expertise: 

Stay abreast of industry trends, emerging technologies, and best practices in data engineering, and incorporate them into our data engineering strategy. 

Provide technical guidance and expertise to the team in areas such as data modeling, ETL/ELT processes, data integration, data ingestion and data governance. 

Define and enforce data engineering standards, frameworks, and methodologies to ensure high-quality deliverables and adherence to business requirements. 

Continuously evaluate and enhance the team's technical skills and capabilities through training, mentorship, and knowledge sharing initiatives. 

Bachelor's or master's degree in computer science, engineering, or a related field. 

Proven experience (minimum 4 years) in leading and managing a team of data engineers or related roles. 

In-depth knowledge of data engineering principles, methodologies, and best practices. 

Comprehensive understanding of data platforms, data integration, and data architecture concepts. 

Strong proficiency in programming languages (e.g., Python, Pyspark, SQL) and data processing frameworks (e.g., Apache Spark). 

Used to constant change environments and adaptable to new frameworks of work. 

Experience working with cloud-based platforms (e.g., AWS, Azure, Google Cloud) and knowledge of distributed computing technologies. 

Excellent leadership and communication skills, with the ability to influence and drive change. 

Strong analytical and problem-solving abilities, with the aptitude to strategize and execute complex data engineering projects.