Vice President 1

• Lead and mentor a team of data engineers, fostering a culture of collaboration, innovation, and continuous improvement.
• Set clear objectives, provide guidance, and facilitate the professional growth of team members.
• Drive team performance, ensuring timely delivery of high-quality solutions aligned with business objectives.
• Data Architecture and Infrastructure:

• Design and implement robust, scalable, and efficient data pipelines and systems to support data processing and analytics needs.
• Evaluate and select appropriate technologies and tools to optimize data infrastructure and architecture.
• Ensure adherence to best practices in data modeling, database design, and data warehousing.
• Data Integration and ETL:

• Oversee the development and maintenance of Extract, Transform, Load (ETL) processes to integrate data from various sources into the data warehouse.
• Collaborate with stakeholders to understand data requirements and design solutions to meet analytical and reporting needs.
• Monitor data quality and integrity, implementing strategies to address data anomalies and discrepancies.
• Performance Optimization and Scalability:

• Identify opportunities for performance optimization and scalability improvements in data processing and storage.
• Implement strategies to enhance system reliability, fault tolerance, and disaster recovery capabilities.
• Conduct regular performance tuning and capacity planning exercises to ensure optimal resource utilization.
• Data Security and Compliance:

• Establish and enforce data security policies, procedures, and access controls to safeguard sensitive information.
• Ensure compliance with relevant data privacy regulations and industry standards (e.g., GDPR, HIPAA, CCPA).
• Work closely with legal and compliance teams to address data governance and compliance requirements.
• Cross-functional Collaboration:

• Collaborate with data scientists, analysts, and business stakeholders to understand data needs and deliver actionable insights.
• Partner with software engineers and DevOps teams to integrate data solutions into production systems seamlessly.
• Communicate effectively with technical and non-technical stakeholders, translating complex technical concepts into understandable terms.

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• Proven experience (10+ years) in a leadership role, managing and mentoring a team of data engineers.
• Strong proficiency in data engineering concepts, tools, and technologies (e.g., SQL, Python, ETL frameworks, data warehousing, cloud platforms like Azure Data Bricks, AWS RDS, Glue, etc.).
• Deep understanding of database design, data modeling, and performance optimization techniques.
• Familiarity with data security principles, compliance requirements, and governance frameworks.
• Excellent communication and interpersonal skills, with the ability to collaborate effectively across diverse teams.
• Strong analytical and problem-solving abilities, with a keen attention to detail and quality.
• Experience with agile methodologies and project management practices is desirable.

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