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Pune, Maharashtra, India
Onsite
You don't have an AI story if you don't have your data story. That's where NexusOne comes in.
We're the converged data platform for the AI era — composable by design, built on an open-source foundation, and AI-native from the ground up. One identity, one governance envelope, one operational layer across every mainframe, data lake, warehouse, and streaming system in the business. For the first time, enterprises can bring their existing stack along instead of rebuilding it — and still give AI agents full context across the estate.
What we stand for is simple: sovereign data, interoperable systems, decoupled intelligence — delivered the way modern software should be. No rip-and-replace. No multi-year transformation. Our CEO Anu Jain puts it well: we turn the "ball of yarn" of data integrations into a unified engine — less like assembling car parts, more like buying the car ready to drive. 85+ open-source tools pre-integrated. AI-native automations that deploy and self-heal the stack without human toil. Forward-deployed engineers who build shoulder-to-shoulder with customer teams — hands on keyboards, not just on decks.
It's working, and fast. We're tripling revenue year over year, backed by Insight Partners, and running in production in environments most vendors won't touch. Our platform processes credit risk data for 90%+ of US small businesses — 40M+ — every month. Intent signals for 300M+ subscribers monthly for Africa's largest telco. The data and AI layer for a Top 3 US bank.
We're 100+ people across the US and India, headquartered in Atlanta. We think big, move fast, and don't mistake activity for progress. We hire people who'd rather ship the rocket than brief someone on it.
Check out this podcast of Anu talking about our solution here: https://www.youtube.com/watch?v=g8g50sv5GhQ
We are currently searching for a 100% Hands-on Data Platform Engineer to join our high-performing product team in Pune. As a Data Engineer, you will play a crucial role in providing technical support, resolving complex issues, and maintaining the stability and security of our customers' environments. If you are passionate about Data products running on AWS/Azure/On Prem, and thrive in a fast-paced environment, this opportunity is for you. The ideal candidate will be a proactive problem solver with expertise in Kubernetes platform/strong python/terraform Automation skills and meticulous attention to detail. This person will be intellectually curious with a relentless desire to learn the latest modern data architecture platforms and patterns.
What You are and will work on:
Install, configure, and support NX1 product clusters in cloud (AWS, Azure, GCP) and on-premises environments, ensuring seamless integration and functionality using Kubernetes, Spark, NiFI, Kafka, Airflow, Trino, Hive, Iceberg, Jupyter, yarn, Impala, Ranger and Hbase ensuring robust data protection and compliance.
Maintain, patch, and upgrade existing NX1 product setups in a 24 x 7 environments, ensuring minimal downtime and adherence to best practices.
Configure Datadog/Grafana agents and develop dashboards to monitor and alert operations teams
Manage daily operations with oncall rotations of Nexusone products and cloud-based technologies using open-source Linux-based data technologies.
Evaluate and optimize complex distributed production deployments, identify bottlenecks, and recommend performance enhancements.
Develop and maintain technical documentation, including administration of runbooks and knowledge base articles, to support operational excellence and knowledge sharing.
Work in an agile team and Participate in an on-call rotation, providing expert-level support and troubleshooting for critical issues.
Lead and mentor junior team members, fostering a culture of continuous learning and improvement. Collaborate with cross-functional teams, including data engineers, solution architects, and DevOps, to design and implement scalable data solutions.
Stay current with emerging technologies and industry trends, applying this knowledge to improve the CDP environment and drive innovation.
General expectation:
Minimum of 5 years of experience in installing and administering Data Platform (Cloudera, Databricks, snowflake) or using open-source tools, with a proven track record of managing large-scale deployments.
Hands-on experience with python/terraform automation skills for open-source Linux-based data technologies.
Proven ability to build and support solutions across major cloud platforms (AWS, Azure, GCP), leveraging cloud-native tools and open source for optimal performance.
Experience integrating Azure Active Directory with FreeIPA and other directory services such as LDAP, enhancing security and user management.
Up-to-date knowledge of the Hadoop Big Data ecosystem, staying current with the latest technologies and best practices.
Excellent troubleshooting skills, with a thorough understanding of capacity planning, identifying bottlenecks, and optimizing memory utilization, CPU usage, OS performance, storage, and network configurations.
In-depth understanding of both on-premise and cloud network architectures, ensuring seamless integration and efficient data flow.
Strong analytical and problem-solving abilities, capable of diagnosing and resolving complex technical issues efficiently.
Nice to have: Cloudera/Databricks/Snowflake Administrator certification is a plus.
Prior experience as a support or development engineer with a focus on Data, Analytics, and AI.
At Nexus, we value people who want to grow — and support each other while doing so.
You can expect:
A collaborative team culture built on curiosity and respect
Challenging work where your contributions clearly matter
A leadership team that invests in learning and development
The opportunity to work at the intersection of cloud, data, and AI innovation
If this role sounds like a great fit — or even close to one — we’d love to hear from you. We know that no candidate checks every single box, and we’re excited to meet people who bring curiosity, talent, and a desire to build meaningful work together.
