[Hiring] Staff Data Engineer @Meeru AI Inc

Role Description

We are looking for a Staff Data Engineer to build and own the major subsystems of the data foundation — the pipelines, connectors, and curated models that feed the platform's analytics and AI layers. You take the data architecture and standards set by the data lead and turn them into robust, production-grade systems that don't break and don't lie about the numbers.

• You own significant pieces of the platform end to end complex transformations over the warehouse, source integrations for new customer systems, and the reconciliation and lineage that prove the curated model ties back to source.
• This is a hands-on, high-ownership engineering role with a clear path toward Senior Staff.

Qualifications

• 7+ years in data engineering.
• Expert SQL and data modeling.
• dbt in production.
• Production orchestration with Airflow or Dagster.
• Warehouse internals and performance tuning.
• A bias toward correctness.
• Solid Python.
• Comfort with messy source systems.
• Collaboration and mentorship.

Requirements

• You've owned complex, production pipelines end to end, including how they perform, how reliable they are and what they cost to run.
• You write complex, set-based transformations over a cloud warehouse (Snowflake, BigQuery, PostgreSQL or similar) and design models other teams build on.
• You've built and maintained real dbt projects, including incremental models that refresh efficiently instead of rebuilding everything.
• You design DAGs that are safe to rerun and backfill.
• You know why a query is slow or expensive on large datasets and how to fix it.
• You treat data tests, reconciliation against source and lineage as core to the job, and you build pipelines that are idempotent and reproducible.
• Enough Python to write pipeline code, tests and tooling that others can maintain.
• You've integrated real-world sources with inconsistent data and changing schemas, and kept downstream models stable.
• You agree data contracts with backend and AI teams, review peers' work and mentor senior and mid-level engineers.

Benefits

• Nice to have ERP and financial data experience with NetSuite, SAP, Oracle or Workday, or with finance data such as general ledger, accounts payable, payroll and HRIS.
• CDC and managed ingestion experience with Change-data-capture pipelines or tools like Fivetran.
• Multi-cloud and customer-hosted deployments across AWS, Azure and GCP.
• A wider warehouse range including Oracle ADW, Apache Pinot or MySQL alongside the main warehouses.
• FinTech or financial-services exposure.
• Reusable integration frameworks experience.
• Test and synthetic data experience for regression testing.
• Interest in architectural ownership.