Data Engineering Lead

The Data Engineering Lead’s role is to spearhead our data engineering efforts, utilizing expertise in Apache Airflow, Snowflake, and team leadership.

This role involves not only hands-on technical responsibilities but also leadership in guiding, mentoring, and managing a team of data engineers to architect and maintain robust data solutions.

✅ Responsibilities:

✔️Leadership: Lead the design, development, and maintenance of scalable data pipelines using Apache Airflow and Snowflake. Provide technical guidance, best practices, and mentorship to the data engineering team.

✔️Team management: Manage a team of data engineers, fostering a collaborative and innovative environment. Assign tasks, set goals, and conduct performance evaluations to ensure the team's success and growth.

✔️Architecture and Strategy: Drive the architecture and strategy for data infrastructure, ensuring scalability, reliability, and efficiency. Collaborate with cross-functional teams to align data engineering initiatives with business objectives.

✔️Data warehousing expertise: Oversee Snowflake data warehouse management, including schema design, optimization, security, and performance tuning. Ensure adherence to best practices and governance standards.

✔️ETL Implementation: Lead the implementation of complex data workflows and scheduling using Airflow, ensuring robustness, monitoring, and optimization.

✔️Collaboration and Communication: Collaborate with stakeholders, data scientists, analysts, and other teams to understand data requirements. Communicate effectively to translate business needs into technical solutions.

✔️Continuous Improvements: Drive continuous improvement initiatives, identify areas for enhancement, and implement best practices to optimize data engineering processes and workflows.

✅ Requirements:

✔️Technical Expertise: Proven experience with Apache Airflow (MWAA) and Snowflake, including designing and implementing scalable data pipelines and data warehouse solutions.

✔️Cloud-Based Stack: Hands-on experience with AWS services (especially S3 and MWAA), Python, and SQL within cloud-based environments.

✔️Collaboration & Communication: Strong interpersonal skills with the ability to work effectively across cross-functional teams and communicate complex technical concepts to both technical and non-technical stakeholders.

✔️Strategic Mindset: Ability to align technical solutions with business goals, contributing to innovation and efficiency across data engineering processes.

✔️Analytical & Problem-Solving Skills: Strong troubleshooting abilities, with a focus on optimizing data workflows and maintaining data accuracy and integrity.