Lead Data Engineer

The Lead Data Engineer is a pivotal leadership role responsible for overseeing the design and architecture of scalable, robust data solutions that meet evolving business requirements. You will lead a team of data engineers in building, optimizing, and maintaining data platforms such as Snowflake and Databricks, while ensuring the implementation of best practices for data security, governance, and compliance. Your expertise in data architecture, software engineering, and big data technologies (Hadoop, Spark, Kafka, etc.) will enable you to provide strategic direction, foster a high-performing team, and champion innovation across the organization’s data landscape.

• Lead, mentor, and develop a team of data engineers, fostering a culture of continuous improvement and innovation.
• Design, develop, and manage data pipelines, architectures, and infrastructure, ensuring scalability, performance, and reliability.
• Oversee the implementation and optimization of data warehouses, data lakes, and other storage solutions, particularly leveraging Snowflake and Databricks.
• Collaborate with cross-functional stakeholders to understand business objectives, translating them into effective and scalable data engineering solutions.
• Ensure adherence to best practices in ETL, data pipeline architecture, and system performance to support advanced analytics, reporting, and business intelligence initiatives.
• Evaluate and introduce new data platforms, tools, or solutions as needed, while maintaining and enhancing existing systems.
• Champion data governance, security, and compliance initiatives, ensuring the integrity and protection of data assets across the organization.
• Stay current with industry trends, emerging technologies, and best practices in big data, cloud data platforms, and data engineering methodologies.

Job Qualifications:

• 5-8 years of experience in data engineering with a strong track record of leading complex projects and teams.
• Advanced proficiency in programming languages such as Python, Java, or Scala, with demonstrated expertise in software engineering best practices.
• Extensive experience with data warehouse technologies, particularly Snowflake and Databricks, including optimization and strategic roadmap development.
• Deep expertise in big data technologies such as Hadoop, Spark, and Hive, with practical experience in managing and optimizing large-scale data environments.
• Experience with real-time data streaming and processing using tools like Apache Kafka, with a focus on event-driven architectures.
• Advanced understanding of data modeling, ETL processes, and data pipeline architecture, with a track record of applying best practices.
• Proven problem-solving skills, with the ability to troubleshoot and resolve complex data issues and provide strategic solutions.
• Excellent communication and leadership skills, with experience mentoring junior engineers and leading cross-functional teams.
• Proven ability to work independently while also leading collaborative efforts within a team.
• Experience in driving the adoption of new tools and technologies and integrating them into existing data engineering practices.
• Must be willing to work in Ortigas, Pasig (Hybrid Work Setup).