Lead SDET | Open Source Data Platform

Posted 21 Days Ago
Be an Early Applicant
2 Locations
60K-100K
Senior level
Software
The Role
As Lead SDET, oversee quality assurance for big data systems, develop automated test strategies, and mentor junior team members. Focus on test automation and performance tuning to ensure high-quality standards.
Summary Generated by Built In

About Us 


Acceldata is the market leader in Enterprise Data Observability. Founded in 2018, Silicon Valley-based Acceldata has developed the world's first Enterprise Data Observability Platform to help build and operate great data products.


Enterprise Data Observability is at the intersection of today’s hottest and most crucial technologies such as AI, LLMs, Analytics, and DataOps. Acceldata provides mission-critical capabilities that deliver highly trusted and reliable data to power enterprise data products.


Delivered as a SaaS product, Acceldata's solutions have been embraced by global customers, such as HPE, HSBC, Visa, Freddie Mac, Manulife, Workday, Oracle, PubMatic, PhonePe (Walmart), Hersheys, Dun & Bradstreet, and many more. Acceldata is a Series-C funded company whose investors include Insight Partners, March Capital, Lightspeed, Sorenson Ventures, Industry Ventures, and Emergent Ventures.


About the Role: We are looking for an experienced Lead SDET for our ODP, specializing in ensuring the quality and performance of large-scale data systems.


In this role, you will work closely with development and operations teams to design and execute comprehensive test strategies for Open Source Data Platform (ODP), including Hadoop, Spark, Hive, Kafka, and other related technologies. You will focus on test automation, performance tuning, and identifying bottlenecks in distributed data systems.


Your key responsibilities will include writing test plans, creating automated test scripts, and conducting functional, regression, and performance testing. You will be responsible for identifying and resolving defects, ensuring data integrity, and improving testing processes. Strong collaboration skills are essential as you will be interacting with cross-functional teams and driving quality initiatives. Your work will directly contribute to maintaining high-quality standards for big data solutions and enhancing their reliability at scale.

You are a great fit for this role if you have

  • Proven expertise in Quality Engineering, with a strong background in test automation, performance testing, and defect management across multiple data platforms.
  • A proactive mindset to define and implement comprehensive test strategies that ensure the highest quality standards are met.
  • Experience in working with both functional and non-functional testing, with a particular focus on automated test development.
  • A collaborative team player with the ability to effectively work cross-functionally with development teams to resolve issues and deliver timely fixes.
  • Strong communication skills with the ability to mentor junior engineers and share knowledge to improve testing practices across the team.
  • A commitment to continuous improvement, with the ability to analyze testing processes and recommend enhancements to align with industry best practices.
  • Ability to quickly learn new technologies

What we look for:

  • 6-10 years of hands-on experience in quality engineering and quality assurance, focusing on test automation, performance testing, and defect management across multiple data platforms
  • Proficiency in programming languages such as Java, Python, or Scala for writing test scripts and automating test cases with hands-on experience in developing automated tests using other test automation frameworks, ensuring robust and scalable test suites.
  • Proven ability to define and execute comprehensive test strategies, including writing test plans, test cases, and scripts for both functional and non-functional testing to ensure predictable delivery of high-quality products and solutions 
  • Experience with version control systems like Git and CI/CD tools such as Jenkins or GitLab CI to manage code changes and automate test execution within the development pipeline.
  • Expertise in identifying, tracking, and resolving defects and issues, collaborating closely with developers and product teams to ensure timely fixes.
  • Strong communication skills with the ability to work cross-functionally with development teams and mentor junior team members to improve testing practices and tools.
  • Ability to analyze testing processes, recommend improvements and ensure the testing environment aligns with industry best practices, contributing to the overall quality of software.

Acceldata is an equal-opportunity employer


At Acceldata, we are committed to providing equal employment opportunities regardless of job history, disability, gender identity, religion, race, color, caste, marital/parental status, veteran status, or any other special status. We stand against the discrimination of employees and individuals and are proud to be an equitable workplace that welcomes individuals from all walks of life if they fit the designated roles and responsibilities.


#LifeAtAcceldata is all about working with some of the best minds in the industry and experiencing a culture that values an ‘out-of-the-box’ mindset. If you want to push boundaries, learn continuously, and grow to be the best version of yourself, Acceldata is the place to be! 

Top Skills

Git
Gitlab Ci
Hadoop
Hive
Java
Jenkins
Kafka
Python
Scala
Spark
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The Company
HQ: Campbell, CA
226 Employees
On-site Workplace
Year Founded: 2018

What We Do

Founded in 2018, Campbell, CA-based Acceldata has developed the world's first enterprise data observability platform to help enterprises build and operate great data products.

Acceldata's solutions have been embraced by global customers, such as Dun & Bradstreet, Verisk, Oracle, PubMatic, PhonePe (Walmart), and many more.

Acceldata investors include Insight Partners, March Capital, Industry Ventures, Lightspeed, Sorenson Ventures, Sanabil, and Emergent Ventures. Contact us to learn about the benefits of data observability.

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