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Bengaluru, Karnataka, India
Hybrid
Job Description:
We are Omnissa!
The world is evolving fast, and organizations everywhere—from corporations to schools—are under immense pressure to provide flexible, work-from-anywhere solutions. They need IT infrastructure that empowers employees and customers to access applications from any device, on any cloud, all while maintaining top-tier security. That’s where Omnissa comes in.
The Omnissa Platform is the first AI-driven digital work platform that enables smart, seamless and secure work experiences from anywhere. It uniquely integrates multiple industry-leading solutions including Unified Endpoint Management, Virtual Apps and Desktops, Digital Employee Experience, and Security & Compliance through common data, identity, administration, and automation services. Built on the vision of autonomous workspaces - self configuring, self-healing, and self-securing - Omnissa continuously adapts to the way people work, delivering personalized and engaging employee experiences, while optimizing security, IT operations and costs. we're experiencing rapid growth—and this is just the beginning of our journey!
At Omnissa, we’re driven by a shared mission to maximize value for our customers. Our five Core Values guide us: Act in Alignment, Build Trust, Foster Inclusiveness, Drive Efficiency, and Maximize Customer Value—all with the aim of achieving shared success for our clients and our team.
As a global private company with over 4,000 employees, we’re always looking for passionate, talented individuals to join us. If you're ready to make an impact and help shape the future of work, we’d love to hear from you!
What is the opportunity?
You will join the team building and operating Omnissa's Enterprise Data Lakehouse. As an individual contributor, you will design and ship pipelines, models, and analytics that power Enterprise reporting (ARR, Bookings, Revenue, GTM, and Product telemetry) and increasingly support our AI initiatives.
What you'll do
Build and operate end-to-end data pipelines on the Lakehouse — ingestion, transformation, and serving — across AWS and Databricks.
Design and develop interactive, insightful dashboards and reports in Tableau/Superset for a mixed technical and business audience.
Write efficient, scalable, secure SQL and Python, processing large datasets with Databricks (Spark) and federated engines like Starburst/Trino/AWS Athena.
Model and manage data in open table formats (Apache Iceberg, Delta Lake), optimizing for cost and performance.
Orchestrate workflows with Apache Airflow and Databricks Workflows; ship changes through GitHub Actions CI/CD.
Apply data governance, data quality, and metadata practices using Unity Catalog and/or Alation (cataloging, lineage, access policies).
Partner with analysts, product, and business stakeholders — translating business questions into robust data solutions.
Contribute to AI/GenAI efforts by preparing data foundations for RAG and agentic use cases, and adopting AI-assisted engineering in day-to-day delivery.
Must have Skills : -
2–5 years in Data Engineering & Analytics.
Strong proficiency in SQL and Python.
Databricks depth: Unity CatLog, Delta Live Tables / declarative pipelines, Workflows, notebooks.
Hands-on Apache Spark for pipeline development.
Experience with large datasets via Starburst/Trino/AWS Athena.
Exposure to the AWS data stack (S3, Glue, Athena, EMR) and Apache Airflow.
Familiarity with Apache Iceberg or other table formats (Delta Lake, Hudi).
CI/CD experience with GitHub Actions.
Dashboarding experience in Tableau/Superset/PowerBI.
Strong communication skills and the ability to translate business questions into data solutions.
Nice to have : -
GenAI/LLM awareness — RAG patterns, embeddings/vector stores, and familiarity with agentic frameworks and MCP-based tooling; interest in building the data layer that powers AI agents.
Fluency with AI-assisted development (e.g., coding copilots / Claude Code) to accelerate delivery.
Comfort with Agile and DevOps ways of working.
What you'll bring to Omnissa
Genuine drive to build on a modern Data Lakehouse and analytics platform.
Excellent verbal and written communication.
Strong analytical and problem-solving abilities, with keen attention to detail.
An ownership mindset — designing highly efficient code with scalability, performance, security, and quality built in.
Ability to work independently and juggle multiple priorities in a fast-paced environment.
Curiosity about applying AI/GenAI to real enterprise data problems.