
Senior Software Engineer - Data Platform
closed
Glassdoor
Summary
Join Glassdoor as a Senior Software Engineer and help build the next generation data platform for Glassdoor and Fishbowl products. This transformational role involves introducing best practices in software development, championing a culture of quality, mentoring junior engineers, and conducting code and architecture reviews. You will also be responsible for setting and enforcing best practices, ensuring platform stability, and introducing a robust data quality strategy. This role requires 4+ years of experience in software engineering, strong data product and business sense, and expertise in various technologies including container orchestration, AWS cloud services, Hadoop, DevOps, and data fundamentals. The ideal candidate will also possess strong AIOps experience and proficiency in managing GPU instances. Glassdoor offers a competitive salary, annual bonus, generous RSUs, comprehensive health and wellness benefits, generous paid time off, and a flexible work environment.
Requirements
- 4+ 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
- A team player outlook, with a growth mindset and an impact-driven approach
- 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, ClickHouse, and/or Snowflake
- 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
Responsibilities
- 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
- Youβll 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
- Youβll mentor junior engineers, challenging their technical skills to help them grow into well-rounded engineers
- Youβll 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
Preferred Qualifications
- Experience with hosting, managing, and deploying LLMs a plus AWS Bedrock, LangChain, and more
- Automated batch training of ML models a plus Airflow, KubeFlow, MLFlow etc
Benefits
- Base salary range*: $118,400 - $157,300
- 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
- With flexible hours and a where-to-work policy, Glassdoor allows you to take on professional and personal responsibilities β enhancing both productivity and your well-being
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