Who we are

80% of the workers across the globe are Deskless. These are the people who keep our lights on and gas flowing build roads and bridges run our manufacturing factories ensure that we get healthcare service and provide us with reliable phone and internet connectivity. As entrepreneurs have we considered solving their problems and making them more productive

Zinier is a company on a mission to empower frontline workers - and the people supporting them - to achieve greater things for themselves and the world around them. With the majority of workers worldwide being deskless Zinier recognizes the need for Technology Equity to improve the lives and productivity of these workers who keep the world up and running.

We are a remote-first global team headquartered in Silicon Valley with a hybrid workforce across the United States Canada Europe Latin America Singapore and Bangalore India with leading investors that include Accel ICONIQ Capital Founders Fund Newfund Capital NGP Capital Tiger Global Management and Qualcomm Ventures LLC.

What we are looking for

Do you get excited about transforming messy fragmented data into a clean scalable foundation that entire teams can build on Are you the kind of engineer who sees a dozen bespoke schemas and thinks I can normalise this rather than thats just how it is Zinier is searching for a hands-on technically excellent Senior Data Engineer who wants to build the data platform that powers our next chapter of growth.

In this high-impact role youll be the architect and builder behind a medallion data architecture (Bronze Silver Gold) on AWS that turns our client deploymentseach with its own quirksinto a unified governed data estate. Youll design CDC pipelines build ETL transformations model star schemas for self-serve BI and lay the groundwork for AI/ML capabilities.

This isnt a maintain-the-dashboard role. Youll be building from the foundations upco-designing the canonical ERD with Solutions and Product migrating legacy schemas and standing up infrastructure that cuts QBR preparation from four weeks to under two days. Youll need to think like an architect one moment and debug a Glue job the next.

Bring your builder mentality your first-principles thinking and your genuine passion for data engineering done right. This is your opportunity to define the data platform for a field service management product used by some of the worlds largest infrastructure operators.

Where you are located

Based in India ideally Bangalore able to collaborate with engineering data and product teams across time zones as needed.

What the role offers

• Design and own the canonical data model co-create the normalised ERD (3NF) with Solutions and Product defining naming conventions data types and relationship standards that all deployments conform to
• Build the medallion data platform (Bronze Silver Gold) on AWS using S3 DMS Glue Redshift Serverless and QuickSight from CDC ingestion through to self-serve dashboards
• Develop and maintain CDC pipelines and ETL jobs that ingest data from Amazon RDS apply business logic calculate KPIs and produce clean analytics-ready star schemas
• Migrate client schemas to the standard model starting with a pilot account and scaling across all accounts with row-level tenant isolation. Each client deployment carries its own schema customisations and configuration variations; a core challenge of this role is normalising divergent client data models into the canonical ERD without losing client-specific fidelity
• Enable self-serve BI for Customer Success build the Gold-layer flat marts and analytics-ready schemas that enable self-serve QuickSight dashboards so the CS team can generate QBR materials in under two days without specialist involvement
• Establish data governance processes including change control for schema modifications a data dictionary cataloging standards via Glue Data Catalog and audit-ready data lineage
• Lay the data foundation for AI/ML ensure clean historical data pipelines that support future AI use cases and cross-client benchmarking models
• Collaborate cross-functionally with Product Engineering on schema migration Solutions on ERD validation and regression testing and the AI team on model training data requirements

What youll bring to the role

• 510 years of data engineering experience in a product or SaaS company; proven track record building production data platforms warehouses or lake architectures from the ground up
• Domain context is a plus: prior experience in FSM field operations utilities telecom or industrial SaaS is a plus youll be modelling data for entities like Work Orders Technician schedules Assets and SLA events
• Strong data modelling fundamentals: experienced in designing normalised (3NF) operational schemas and dimensional/star schemas for analytics; comfortable navigating schema divergence across multi-tenant deployments
• Pipeline and orchestration fluency: CDC ELT/ETL patterns job orchestration idempotent pipelines and schema evolution handling
• Strong programming skills in Python Go or Java with hands-on experience building and maintaining data pipelines transformation logic and automation in production environments
• Deep AWS data stack expertise: hands-on with S3 Glue (ETL Data Catalog) DMS Redshift (or Redshift Serverless) Athena and QuickSight or comparable experience with equivalent tools and a willingness to ramp quickly
• First-principles problem solver: strong technical judgement with the ability to make pragmatic architectural decisions balancing long-term scalability with near-term delivery
• Governance and quality mindset: experience implementing data cataloguing lineage tracking access controls and change management processes
• Hustler mentality with engineering craft: resourceful persistent and pragmatic; you ship working systems not just designs. Comfortable navigating ambiguity in a fast-paced environment
• Excellent communication and collaboration: ability to work across Data Product Solutions and AI teams; distil technical complexity into clear decisions for non-technical stakeholders
• Be Hungry. Be Humble. Be Honest. And Hustle.

Own the data platform. Build the foundation. Be the reason our customers and teams thrive.