[Hiring] Data Engineer @Weekday AI

Role Description

We are seeking an accomplished Engineering Manager – Data Engineering to lead the design, development, and scaling of robust data platforms and pipelines. This role is ideal for a seasoned professional who combines deep technical expertise in data engineering with strong leadership capabilities. You will be responsible for driving data strategy, mentoring high-performing teams, and delivering scalable data solutions that power business intelligence, analytics, and advanced applications such as AI/ML.

• Lead and manage a team of data engineers, fostering a culture of innovation, ownership, and continuous improvement.
• Define and execute the data engineering roadmap aligned with organizational goals and product strategy.
• Architect, design, and oversee the implementation of scalable, reliable, and high-performance data pipelines and data platforms.
• Collaborate with cross-functional teams including Product, Analytics, Data Science, and DevOps to deliver end-to-end data solutions.
• Establish best practices for data governance, data quality, security, and compliance.
• Drive the adoption of modern data technologies and frameworks, ensuring systems are future-ready and cost-efficient.
• Review system architecture and code to ensure scalability, maintainability, and performance optimization.
• Manage stakeholder expectations, prioritize initiatives, and ensure timely delivery of projects.
• Mentor team members, support career growth, and build leadership within the team.
• Monitor and improve system reliability, uptime, and performance through proactive measures and observability tools.

Qualifications

• Strong experience in data engineering, including building large-scale data pipelines and distributed systems.
• Hands-on expertise with modern data stack technologies such as SQL/NoSQL databases, ETL/ELT tools, and data warehousing solutions (e.g., Snowflake, BigQuery, Redshift).
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with big data technologies like Apache Spark, Hadoop, or Kafka.
• Deep understanding of cloud platforms such as AWS, Azure, or Google Cloud.
• Strong knowledge of data modeling, data architecture, and data lifecycle management.
• Experience implementing data governance, security, and compliance frameworks.
• Familiarity with CI/CD pipelines, DevOps practices, and infrastructure-as-code tools.
• Proven track record of leading and scaling high-performing engineering teams.

Requirements

• Demonstrated ability to lead teams of 8–20 engineers, including senior and lead engineers.
• Strong decision-making skills with the ability to balance technical depth and business priorities.
• Excellent communication and stakeholder management skills.
• Experience in agile development methodologies and delivering large-scale projects.
• Ability to influence technical direction and drive organizational change.

Preferred Qualifications

• Experience in building data platforms for AI/ML use cases.
• Exposure to real-time data processing and streaming architectures.
• Prior experience in enterprise-scale or high-growth environments.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.