Flexera develops technology asset management and optimization software for organizations managing complex IT environments. Its Flexera One platform brings together visibility across software, SaaS, hardware, and cloud assets, helping teams track SaaS spending, manage software licenses, and oversee the IT asset lifecycle. Flexera also connects IT asset management with FinOps practices, giving finance and technology teams tools to understand cloud costs, improve resource use, and address security and regulatory risks. Its products serve enterprises working to make informed decisions about technology spending and operations.
Staff Data Engineer, Databricks Lakehouse (India, Hybrid)
Shape Flexera’s Databricks lakehouse and Python backend platforms. Support enterprise SaaS products for technology cost optimization, analytics, and AI/ML.
Opis
- Lead the architecture and development of scalable, cloud-native backend systems and APIs.
- Build and operate Python API services, such as FastAPI, that provide access to data platform capabilities.
- Design and tune PostgreSQL schemas, indexes, queries, and schema migrations.
- Set technical direction for the reliability, scalability, performance, and cost efficiency of data-intensive workloads.
- Lead complex backend projects from initial design through production launch and ongoing operations.
- Maintain CI/CD pipelines with GitHub Actions and Terraform, and deploy changes to production.
- Troubleshoot issues across APIs, databases, and data pipelines.
- Work with data engineering, frontend, platform, and SRE teams.
- Set engineering standards for code quality, testing, CI/CD, observability, and operational practices.
- Advise teams on technical designs and implementations.
- Mentor engineers at junior and senior levels.
- Apply current practices in backend systems, cloud platforms, and large-scale data engineering.
- Guide the design and performance of Flexera’s Databricks lakehouse for analytics, AI/ML, and product development.
Zahteve
- Bachelor’s or master’s degree in computer science or engineering, or equivalent practical experience.
- At least 8 years of backend engineering experience.
- Hands-on experience developing Python applications and services, including production APIs.
- Strong RDBMS skills, preferably with PostgreSQL, including schema design, complex query development and tuning, migration tools such as Flyway, and query-plan performance analysis.
- Experience designing, building, deploying, and operating REST APIs with FastAPI, Flask, or an equivalent framework.
- Experience building and maintaining CI/CD deployment automation with GitHub Actions, Azure DevOps, or similar tools.
- Infrastructure-as-code experience with Terraform or a comparable tool.
- Ability to provision cloud resources independently.
- Experience building large-scale data or analytics platforms.
- Strong experience with observability, monitoring, distributed tracing, query profiling, and latency troubleshooting.
- Experience with security, compliance, and enterprise SaaS requirements.
- Experience in FinOps, cloud cost optimization, or enterprise SaaS platforms.
- AWS experience, including ECS/Fargate, RDS, S3, IAM, and Secrets Manager.
- Experience building AI-powered backend systems, including LLM-based or agent-driven workflows.
- Preferred: experience with Power BI Direct Lake mode and semantic modeling for lakehouse analytics.
- Preferred: familiarity with Mosaic AI, Databricks GenAI capabilities, or feature store implementations.
- Preferred: open-source Spark contributions, Databricks community content, or credentials such as Databricks Certified Data Engineer Professional.
Ugodnosti
- Competitive compensation.
- Flexible work arrangements.
- Defined growth paths for senior technical leaders.
- Collaborative, inclusive, technically focused culture.
- Equal opportunity employment.
- Workplace accommodations available upon request.