- Type
- Full-time
- Department
- IT
- Seniority
- Manager
- Education
- Bachelor
- Source
- Keka
Description
Technical Product Manager- Data Engineering
- Location: Bengaluru
- Experience: 7–10 years
- Function: Product Management-Data Platform & Engineering
- Employment Type: Full-time
About Zluri: Securing the AI Future
Every enterprise is deploying AI agents. Almost none of them know what those agents can access.
Zluri is building the Identity Control Plane for the AI Era - a unified platform that brings real-time visibility and governance to every identity in an organisation, human and non-human alike. We combine Identity Security Posture Management (ISPM), Identity Visibility & Intelligence (IVIP), and Identity Governance into a single platform powered by a Context Graph architecture.
While others build agents to do the work, we build the infrastructure to keep them from going rogue.
We're a Series-B startup backed by Lightspeed, MassMutual Ventures, Endiya Partners, and Kalaari Capital, trusted by 200+ enterprise customers to secure their identity landscape. If you're excited to help define how the world governs identity in an AI-first future, we'd love to talk.
Role Summary:
We are looking for a highly technical and data-driven Technical Product Manager -Data Engineering who can operate at the intersection of Product, Data Engineering, Architecture, & Business. The ideal candidate will own the product vision and roadmap for Zluri's data platform and data engineering ecosystem, working closely with Data Engineers, Backend Engineers, Analytics, and Security.
We’re looking for someone who can go deep into technical discussions, understand modern data architectures, translate complex data problems into product requirements, and drive execution from problem discovery through adoption and measurable business outcomes.
Key Responsibilities:
Data Platform Product Strategy
- Own and drive the roadmap for Zluri's data platform, data infrastructure, and data products.
- Define product vision, strategy, priorities, & success metrics for data engineering initiatives.
- Identify opportunities to improve data availability, quality, reliability, scalability, and accessibility.
Technical Product Management
- Partner closely with the Data Engineering team to define scalable technical solutions.
- Develop detailed PRDs, product requirements, user stories, acceptance criteria, and technical specifications.
- Understand and contribute to discussions around data pipelines, ETL/ELT, data warehouses/lakes, APIs, event-driven architectures, data models, orchestration, and real-time/near-real-time processing.
Data Architecture & Engineering
- Work with engineering teams on data ingestion from multiple internal and external sources.
- Define requirements for data transformation, data modeling, lineage, metadata, and data observability.
- Drive improvements in pipeline performance, scalability, availability, and cost efficiency.
- Continuously analysing market trends to identify emerging opportunities, assess competitive dynamics, and drive informed strategic decisions.
- Prioritising the data platform over other product initiatives within the organisation to maintain its strategic focus and competitive advantage.
Data Quality & Governance
- Establish product requirements and standards for data quality, accuracy, consistency, freshness, and reliability.
- Partner with Data Governance, Security, and Engineering teams on data access, privacy, governance, and compliance.
- Drive initiatives around data lineage, cataloging, ownership, monitoring, and observability.
- Define and track data quality KPIs and SLAs.
Cross-functional Product Leadership
- Collaborate with Engineering, Data Science, Analytics, Security, Customer Success, and Business teams.
- Translate business problems into scalable data products and platform capabilities.
- Communicate technical concepts effectively to both technical and non-technical stakeholders.
- Manage competing priorities and align multiple teams.
Product Discovery & Execution
- Conduct discovery with internal users, engineering teams, and business stakeholders to identify data-related pain points.
- Prioritise initiatives based on business impact, customer value, engineering effort, and strategic importance.
- Own initiatives end to end—from discovery and roadmap definition to launch, adoption, and measurement.
- Establish product metrics and continuously optimize platform adoption and performance.
Qualification and Experience:
- Education: Bachelor's degree in Business, Engineering, or a related field.
- Experience: 7–10 years in Product Management, Technical Product Management, Data Product Management, Data Engineering, or a closely related domain.
- Experience working in a B2B SaaS/enterprise technology environment is a must.
- Technical Skills: Strong understanding of data engineering concepts and modern data architectures.
- Experience working closely with Data Engineering / Platform Engineering teams.
- Strong understanding of: Data pipelines and ETL/ELT, Batch and streaming architectures, Data modelling, APIs and event-driven systems, Data orchestration, Data quality and observability, Data governance and lineage
- Ability to read and understand SQL and work comfortably with technical teams; exposure to Python is a plus.
- Experience with cloud data platforms such as AWS, GCP, or Azure.
- Exposure to technologies such as Snowflake, Databricks, Kafka, Spark, Airflow, or similar modern data-stack technologies is highly desirable.
- Strong analytical and problem-solving skills.
- Excellent stakeholder management and communication skills.
- Demonstrated ability to translate complex technical problems into clear product requirements and roadmaps.
Note: This role is intended for candidates who bring a strong combination of technical depth + product management expertise, rather than a conventional business/product management profile.
Empowering Diversity, Championing Inclusivity
Zluri values diversity and inclusivity and fosters an environment where every individual feels welcome and respected. We are an Equal Opportunity Employer, providing fair consideration to all qualified applicants, regardless of race, colour, religion, gender, gender identity, sexual orientation, national origin, genetics, disability, age, or veteran status.
Skills
PythonAWSAzureGCPSQLSparkAirflowSnowflakeDatabricksData ScienceData EngineeringETLCompliance