Customer Success Manager
Please note- This is for Bangalore location
As a Customer Success Manager at DataPelago, you will play a critical role in ensuring our customers achieve meaningful outcomes using our advanced analytics engine built for Lakehouse platforms. You will partner closely with clients to understand their goals, drive adoption of our product, and deliver long-term value through ongoing engagement, technical enablement, and strategic guidance.
This is a hands-on role that requires a deep understanding of data engineering, analytics, Lakehouse architectures (e.g., Delta Lake, Apache Iceberg), and related cloud technologies. You will serve as a trusted advisor to your customers, helping them to integrate, optimize, and expand their use of DataPelago within their data ecosystem.
Key Responsibilities
- Serve as the primary post-sales point of contact and advocate for customers, ensuring a seamless onboarding and implementation process.
- Build deep relationships with technical and business stakeholders to align product capabilities with customer goals.
- Drive product adoption and usage, delivering measurable business outcomes that demonstrate the value of DataPelago.
- Proactively identify risks to customer success and create strategies to mitigate churn while maximizing growth opportunities.
- Partner with sales, product, and engineering teams to communicate customer feedback and drive continuous product improvement.
- Guide clients in co-existing and integrating DataPelago alongside other analytics engines (e.g., Databricks, Snowflake, Dremio) within Lakehouse environments.
- Conduct product walkthroughs, knowledge transfer sessions, and enablement workshops for technical and non-technical teams.
- Support the development of customer reference architectures and case studies based on successful deployments.
- Collaborate with system integrators, consultants, and other partners to ensure joint success in complex enterprise environments.
- Mentor junior team members and contribute to the overall growth of the Customer Success team.
- Handling escalations and production issues
- funneling improvements from bugs encountered in customer environment to bug fixes, features and supportability enhancements in the product.
Qualifications
- Proven experience in customer-facing roles such as Customer Success, Solutions Engineering, Technical Account Management, or Post-Sales Consulting.
- Strong technical acumen in Lakehouse platforms, data engineering, analytics, SQL, and AI/ML.
- Hands-on expertise in public cloud platforms (AWS, Azure, GCP) and common data tools (Spark, Python, Scala, Java).
- Ability to clearly communicate complex technical concepts to both technical and business audiences.
- Experience with onboarding, driving adoption, and demonstrating ROI in enterprise software environments.
- Excellent collaboration and stakeholder management skills.
- Bachelor’s degree in Computer Science, Engineering, or a related field; Master's preferred.
Top Skills
What We Do
DataPelago is redefining how enterprises process data for AI and analytics at scale. As organizations race to operationalize artificial intelligence, they are discovering that the greatest barrier to progress isn’t a lack of models or talent – it’s the infrastructure beneath them. Data pipelines remain fragmented across specialized systems for analytics, AI, and data engineering, each optimized for specific workloads but incapable of operating as a cohesive whole. The result is inefficiency: duplicated data, stranded compute resources, and escalating costs that slow innovation.
DataPelago was founded to solve this challenge. Its flagship product, Nucleus, is the world’s first Universal Data Processing Engine (UDPE) – a new layer that sits between data lakes and query engines to unify data processing within a single, hardware-aware stack. Built from first principles for accelerated computing, Nucleus allows companies to process, move, and activate their data orders of magnitude more efficiently than existing systems.
At its core, Nucleus dynamically orchestrates workloads across heterogeneous compute environments – CPUs, GPUs, TPUs, and FPGAs – ensuring every job runs on the optimal hardware for maximum performance and efficiency. This unified approach eliminates the need to maintain separate infrastructure for different data workloads, dramatically reducing complexity and total cost of ownership by up to 40%.
Nucleus supports structured, unstructured, and semi-structured data in a single environment, enabling AI and analytics workloads to coexist seamlessly. It integrates easily with existing data ecosystems and open-source frameworks, providing enterprises with flexibility and performance without requiring code changes or proprietary lock-in.
With Nucleus, data teams can accelerate queries, streamline pipelines, and scale AI initiatives faster, all while controlling infrastructure spend. Early adopters across industries are leveraging the platform to speed up data preparation, model training, and real-time analytics by up to 10x, turning data from a bottleneck into a competitive advantage.
DataPelago’s mission is to make high-performance, cost-efficient data processing achievable for every enterprise. By bridging the gap between data infrastructure and AI innovation, the company is helping organizations unlock the full potential of their data, laying the foundation for a new era of intelligence at scale.
Why Work With Us
DataPelago is pioneering the world’s first Universal Data Processing Engine, unifying AI and analytics in a single, hardware-aware platform. We’re solving one of the biggest challenges in enterprise AI – making data infrastructure faster, simpler, and more efficient. Join us to build the foundation for the next era of intelligent computing.
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