As a Lead Data Engineer, you will be responsible for designing, implementing, and optimizing complex data pipelines and architectures that drive our AI and analytics platforms. With 10-12 years of experience, you will lead large-scale data initiatives and collaborate with senior leadership to align data strategies with business goals. This role is ideal for someone who thrives on solving complex challenges, optimizing data workflows, and scaling systems to meet growing business needs.

You Will:

• Lead the architecture, design, and implementation of large-scale, high-performance data infrastructure, ensuring scalability and reliability.
• Oversee the development and optimization of ETL processes, data lakes, and data warehousing solutions to support advanced analytics and AI-driven applications.
• Collaborate with cross-functional teams including Data Science, Product, and Engineering to ensure alignment on data strategies and business objectives.
• Establish data governance, security, and best practices to ensure the integrity, accessibility, and safety of all data systems.
• Proactively identify areas for automation and implement solutions to streamline data processing workflows.
• Mentor and guide a team of data engineers, providing technical leadership, code reviews, and best practice enforcement.
• Monitor and optimize system performance, identifying and resolving bottlenecks to ensure efficient data flows.
• Stay up-to-date with emerging technologies and trends in data engineering, applying innovative solutions to enhance system capabilities.
  
  

You’ll Have:

• A bachelor’s or master’s degree in Computer Science, Information Systems, or a related field.
• 10-12 years of hands-on experience in data engineering, with proven expertise in building and managing large-scale data architectures.
• Strong proficiency in modern data engineering technologies such as Hadoop, Spark, Kafka, and cloud-based data solutions (AWS, Google Cloud, or Azure).
• Extensive experience with ETL tools, data warehousing (e.g., Redshift, Snowflake, BigQuery), and distributed systems.
• Expertise in programming languages such as Python, Java, Scala, or similar.
• Deep knowledge of SQL, data modeling, and query optimization techniques.
• A proven track record of leading teams and mentoring junior engineers, driving technical initiatives, and ensuring project success.
• Strong problem-solving skills with the ability to troubleshoot complex issues and optimize performance in large data environments.
  
  

Preferred Qualifications:

• Experience working in AI/ML-driven environments or with AI-powered data applications.
• Familiarity with real-time data processing technologies like Apache Flink, Storm, or Kinesis.
• Expertise in cloud-native data services, serverless architectures, and containerization (Docker, Kubernetes).
• Prior experience implementing and managing data governance frameworks and compliance protocols.
• Strong communication skills with the ability to influence key stakeholders and present technical concepts to non-technical audiences.

Pay Range: $146,000 - $264,000 base salary. Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience.