Staff Software Engineer

About The Role

It is a transformational time at Glassdoor. As we introduce our community offering to the world our data systems must scale to support the significant increase in engagement with the Glassdoor and Fishbowl products. Therefore, our data platform is also going through a transformational shift that sees the re-architecture and design of every piece of infrastructure from stream and batch processing to our data lake and overall data strategy. The Staff Software Engineer that joins the team will be incredibly valuable in helping us build out the next generation data platform that will support Glassdoor and Fishbowl’s many products. This role will report into the Engineering Manager of Data Platform.

What You’ll Do

• Introduce best practices in software development across data engineering and machine learning teams, ensuring technical architecture and design decisions support scalability, performance, and maintainability.
• You'll champion a culture of quality, continuous improvement, and technical mentorship within the team while partnering closely with various other teams across the engineering organization.
• You’ll set and enforce best practices and standards for the data platform team and ensure that our platform runs smoothly while keeping our cloud environment clean.
• You’ll mentor junior and senior engineers, challenging their technical skills to help them grow into well-rounded engineers.
• You’ll conduct regular code and architecture reviews for the data platform team championing new approaches and refining older ones to keep us at the cutting edge of technology.
• Introduce a robust data quality strategy aimed to eradicate poor data from making its way into production.

What You’ll Bring

• A commitment to add to our culture of DEI
• 8+ years of experience in software, platform, DataOps, MLOps engineering or a similar role.Strong data product and business sense to drive decision making that allows you to put yourself in the shoes of the end-user.Strong interpersonal and collaboration skills, with the ability to work effectively across functions and influence decision-making. Experience in stakeholder management and building consensus among diverse groups.
• Expertise in container and container orchestration tools (Docker and/or Kubernetes)
• K8s cluster management
• Performance optimizations
• Updating and deploying helm charts
• Expertise with CI/CD (GitHub Actions, GitLab CI, Jenkins, etc) fundamentals and implementation for big data tools
• Strong AWS cloud fundamentals:
• Experience with IaC (CloudFormation and/or Terraform)
• EMR, S3, EC2, EKS, ECS, ECR, VPC, IAM, Route 53, Kinesis, Lambda, Glue, and more
• Hadoop fundamentals:
• HDFS, Hive, Tez, Spark, and more
• Strong DevOps and SysOps experience
• Networking experience (VPC, network peering, TCP/IP, subnets, etc)
• Monitoring, observability, and alerting with DataDog, CloudWatch, and/or Grafana
• Strong software fundamentals:
• Hands-on development & writing code (Python, Java, Scala, etc)
• Unit testing, mocking, and patching strategies (pytest, unittest, mockito, etc)
• OOP/OOD and software design patterns (factory, facade, builder, adapter, etc)
• Experience with UML diagrams
• Strong data fundamentals:
• Development of custom Airflow operators and libraries
• Maintaining Airflow webserver, scheduler, and metastore
• Maintaining EMR clusters for Hive and Spark workloads
• Snowflake fundamentals
• Streaming data with Kafka and transformations with ksqlDB/Flink
• Experience with TimescaleDB and/or ClickHouse
• Understanding fundamentals of data architecture and modeling
• Strong AIOps experience:
• Understanding of ML Lifecycle
• Understanding of agentic design
• Proficiency in managing GPU instances, managing and monitoring GPUs in cluster environments
• GPU concurrency & time-slicing
• Experience working with tools like MLFlow, Kubeflow, KServe or BentoML
• ML model registries, DVC, etc

Nice to Haves

• Experience with hosting, managing, and deploying LLMs
• AWS Bedrock, LangChain, and more
• Automated batch training of ML models
• Airflow, KubeFlow, MLFlow etc

Compensation and benefits

Base salary range*: $134,400 - $178,500

Glassdoor base salaries are targeted to the market 75th percentile for technical roles and the 65th percentile for non-technical roles. In other words, 65-75% of comparable organizations in our industry will pay less.

Annual bonus target**: 10%

**Bonuses are paid in 6-month intervals, aligning with bi-annual performance reviews

Generous Restricted Stock Units (RSU):

***Restricted Stock Units (RSU) are awarded at hire and may be refreshed annually. Additionally, as a pay-for-performance company, there are additional RSU grant awards for the very top performers.

Health and wellness: 100% employer-paid premiums for employee medical, dental, vision, life, short and long-term disability and select well-being programs, along with 80% employer-paid premiums for all dependents.

• Generous paid time-off programs for birthing and non-birthing parents are provided, along with additional company-sponsored leaves such as paid injury/illness leave, family emergency leave, compassionate leave, and domestic & sexual violence leave.

• Coverage begins at the start of employment. After 48 months of continuous employment, 100% of all premiums for you and your dependents can be employer-paid!

• Wellness programs to support mental, physical, and financial health, such as paid career coaching & mental health therapy, financial coaching, subsidized fitness & wellness appointments, HSA, FSA, commuter benefits, fertility & pregnancy support, employee perks and discounts, legal assistance program, gender-affirming care relocation benefit and work-from-home monthly allowance.

Work/life balance: Open Paid Time Off policy, in addition to 15-20 paid company holidays/year.

Investing in your future: 401(k) plan with a company match up to $5,000 per year, subsidized fertility & family planning services and discounted legal assistance services.