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DevRev

Integrates data engineering with GenAI solutions

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeAustin, TX, USANo salary listedIn-person

About the Job

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
  • 5+ years of software or data engineering experience building production systems.
  • Strong programming experience in one or more general-purpose languages such as Go, Java, C++, Python, or JavaScript, along with strong SQL skills.
  • Strong understanding of data structures, algorithms, and software engineering fundamentals.
  • Experience designing and operating production-grade data pipelines or distributed data systems.
  • Experience working with relational and/or NoSQL databases and understanding their underlying performance and scalability characteristics.
  • Strong ability to independently drive projects from technical design through implementation, deployment, and operation.

Responsibilities

  • Own data architecture for large-scale, high-impact projects, making thoughtful tradeoffs across scalability, reliability, performance, maintainability, and operational cost.
  • Design, build, and operate scalable data pipelines and data systems that reliably ingest, transform, store, and serve large volumes of data.
  • Partner closely with Software Engineering, Data Science, Product Management, and other stakeholders to understand data requirements and translate them into robust technical solutions.
  • Define and own data quality, reliability, and SLA/SLO requirements for datasets and systems within your area of ownership.
  • Design and optimize data models, databases, and complex SQL workloads, with a strong focus on query performance, storage efficiency, and scalability.
  • Build frameworks, tooling, and reusable infrastructure that make it easier for engineers and data consumers to develop and maintain data products.
  • Identify opportunities to leverage data to improve products, customer experiences, and business outcomes, and influence cross-functional teams toward high-impact solutions.
  • Establish and promote engineering best practices around testing, observability, deployment, and operational excellence for data systems.
  • Mentor engineers through technical guidance, design reviews, and actionable feedback, while contributing to a strong engineering culture.

Desired Qualifications

  • Experience designing large-scale data platforms, data warehouses, or distributed data systems.
  • Deep understanding of database architecture, data modeling, query optimization, indexing, partitioning, and storage systems.
  • Experience with cloud data infrastructure and databases, including understanding of performance, scalability, reliability, and cost tradeoffs.
  • Experience building and operating high-throughput or large-scale data pipelines.
  • Experience working with large datasets and optimizing complex SQL queries and data processing workloads.
  • Experience with distributed data technologies such as Kafka, Spark, Flink, Trino/Presto, BigQuery, Snowflake, or similar systems.
  • Strong experience with data quality, observability, monitoring, and production reliability.
  • Experience developing robust testing strategies, including unit, integration, and data quality testing.
  • Experience providing technical mentorship and driving engineering best practices across teams.
  • Master’s degree in Computer Science or a related technical field.

About the Company

DevRev

Integrates data engineering with GenAI solutions

DevRev.ai builds AI-powered data engineering tools to connect data from silos like support, product management, and software development. Its flagship GenAI platform integrates data engineering, knowledge graphs, and customizable language models to automate and streamline business operations. It serves a broad range of clients with tailored AI solutions, charging either one-time project fees or ongoing service subscriptions. The company differentiates itself by offering integrated AI that unifies disparate parts of a business rather than focusing on a single function. The goal is to help organizations improve efficiency and cross-team collaboration through tailored, data-driven AI.

Company size
501-1,000
Company stage
Series A
Total funding
$150.8M
Headquarters
Palo Alto, CA
Founded
2020

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