Senior Manager, Data Engineering

Shark Ninja Operating - Needham, MA

Full-time - Senior

Needham, MA

Professional, Scientific, and Technical Services

About the position

The Senior Manager of Data Engineering at SharkNinja is responsible for leading the design, development, and maintenance of scalable data infrastructure and pipelines. This role involves managing cloud-based platforms, ensuring data quality and governance, and collaborating with various business and technical teams to align data initiatives with company goals. The position also emphasizes team leadership, project management, and the exploration of new data technologies to enhance the company's data capabilities.

Responsibilities

• Lead the design, development, and maintenance of scalable data infrastructure and pipelines.
• Ensure the data architecture aligns with the company's goals for analytics, machine learning, and other data-driven initiatives.
• Manage cloud-based platforms such as AWS, Google Cloud, or Azure for data storage, ETL processes, and integration with internal and external data sources.
• Lead a team of data engineers, providing mentorship, setting objectives, and driving professional development.
• Foster a collaborative environment, ensuring the team works cross-functionally with data scientists, analysts, and business stakeholders to deliver projects effectively.
• Implement best practices for data governance, ensuring high data quality, consistency, and security across all pipelines.
• Oversee data validation processes, data cleansing efforts, and ensure compliance with relevant data privacy regulations (e.g., GDPR).
• Partner with product managers, business leaders, and other departments to understand data needs and deliver solutions that align with business goals.
• Work closely with IT and software engineering teams to ensure seamless integration of data pipelines with other business systems.
• Continuously monitor and improve the performance of data systems, focusing on latency, scalability, and cost-efficiency.
• Develop and enforce standards for system performance monitoring and alerting to prevent data pipeline failures.
• Lead efforts to explore and integrate new data technologies, tools, and platforms that could enhance the company's data capabilities.
• Provide strategic guidance on the adoption of big data, AI, machine learning, and automation to improve data handling and analysis.
• Oversee the end-to-end delivery of data engineering projects, ensuring timely and successful completion.
• Manage resources, timelines, and budgets for large-scale data initiatives.

Requirements

• Strong knowledge of data engineering technologies such as Python, SQL, Spark, Kafka, Hadoop, and data warehouse solutions (e.g., Snowflake, Redshift).
• Proficiency in ETL (Extract, Transform, Load) tools and cloud-based data solutions (AWS Glue, Google BigQuery, Azure Data Factory, etc.).
• Experience with DevOps practices and infrastructure automation tools (e.g., Terraform, Kubernetes) is often required.
• Proven experience leading teams of engineers, fostering a high-performance culture, and managing distributed or global teams is often preferred.
• Strong people management skills, including recruitment, performance management, and fostering growth and innovation within the team.
• Deep understanding of data security best practices and regulatory frameworks like GDPR and CCPA.
• Experience implementing data governance frameworks to ensure data integrity and compliance with legal requirements.
• Ability to communicate complex technical concepts to non-technical stakeholders.
• Experience working with cross-functional teams to align data engineering efforts with business needs.
• Strong business acumen and understanding of how data engineering contributes to broader business goals.
• Proven experience managing large-scale data engineering projects, including resource planning, risk management, and performance tracking.