Staff Software Engineer- Data Ingestion

Accountabilities

• • Identify, architect, and develop scalable, highly performant solutions for large-scale data ingestion, storage, and processing.
  • Lead the refactoring and optimization of existing data pipelines to improve reliability, scalability, maintainability, and query performance.
  • Design and develop next-generation distributed data storage and processing systems capable of supporting large-scale, real-time, and batch workloads.
  • Build robust ETL/ELT and data ingestion architectures that efficiently process complex and high-volume datasets.
  • Develop clean, expressive interfaces and abstractions that simplify access to complex data infrastructure for web applications, analytics, and AI use cases.
  • Work cross-functionally with Product, Engineering, Analytics, and other disciplines to shape product strategy, technical direction, and execution.
  • Establish strong foundations for code architecture, engineering quality, reliability, scalability, and maintainability.
  • Set and uphold engineering processes, standards, and best practices that support consistent delivery of high-quality software.
  • Evaluate database architecture and performance strategies, including partitioning, indexing, replication, sharding, caching, and query optimization.
  • Contribute to architecture reviews and make technical decisions that balance immediate business needs with long-term scalability and maintainability.
  • Design and maintain CI/CD pipelines and engineering workflows that support reliable, automated software delivery.
  • Monitor infrastructure performance, identify bottlenecks, and implement improvements that increase system efficiency and resilience.
  • Mentor and coach engineers, provide technical guidance, and help develop engineering capabilities across the organization.
  • Promote secure, governed, compliant, and reliable approaches to handling enterprise data and distributed infrastructure.

  Requirements

  • Bachelor’s or higher degree in Computer Science, Engineering, or a related technical field.
  • 8+ years of production-level software engineering experience building highly scalable and reliable systems.
  • 4+ years serving as a trusted technical decision-maker within engineering teams, balancing short-term execution with long-term business and technical value.
  • 4+ years of experience working with SQL or other database query languages across large, multi-table datasets.
  • Demonstrated experience architecting, developing, and deploying large-scale distributed systems.
  • Experience working with cloud platforms such as AWS, Azure, or GCP.
  • Strong experience building and maintaining continuous integration and continuous delivery pipelines.
  • Strong familiarity with server-side technologies and programming languages such as Java, Python, Scala, C#, C++, or Go.
  • Extensive experience designing, optimizing, and orchestrating robust data pipelines and ingestion systems for large-scale real-time and batch processing.
  • Experience with data warehouses such as Snowflake or Redshift and analytics technologies such as Spark, SQL, Python, or Databricks.
  • Hands-on experience with containerization technologies including Docker and Kubernetes.
  • Strong understanding of distributed architectures, including event-driven systems and in-memory computing.
  • Deep knowledge of modern database systems and high-performance query optimization techniques, including replication, sharding, partitioning, indexing, and caching.
  • Understanding of data security, governance, and compliance principles.
  • Experience with infrastructure monitoring, performance optimization, and participation in architecture reviews.
  • Strong technical communication, problem-solving, collaboration, and mentoring skills.
  • Ability to operate independently on complex technical challenges while influencing engineering direction across teams.

  Benefits

  • Opportunity to lead the architecture and evolution of large-scale data ingestion and distributed systems.
  • High-impact technical role with significant influence over engineering standards and infrastructure strategy.
  • Opportunity to mentor engineers and shape technical practices across the organization.
  • Exposure to modern cloud, data engineering, distributed systems, and AI-focused infrastructure.
  • Work involving scalable real-time and batch data processing and high-performance query optimization.
  • Benefits and compensation details are not specified in the provided job description and may be discussed during the hiring process.
  • Role requires prolonged periods of sitting and extensive computer and keyboard use, with occasional walking and lifting as needed.