- Company Name
- Mindwire Systems Ltd
- Job Title
- Senior Data Engineer – Embedded Analytics & Data Platform
- Job Description
-
Job title: Senior Data Engineer – Embedded Analytics & Data Platform
Role Summary: Own the design, build, and operation of a multi‑tenant data warehouse that powers embedded, self‑service analytics within a SaaS product. Deliver high‑performance queries, robust governance, and AI readiness while enabling customers to explore data directly in the client UI without external tools.
Expectations: Deliver a scalable, secure, and performant analytics platform; maintain data quality and reliability; collaborate with product, UX, and application teams; future‑proof the architecture for AI/ML workloads; and provide clear documentation for customers and internal stakeholders.
Key Responsibilities:
- Architect and implement a Snowflake/BigQuery/Redshift/Databricks warehouse optimized for embedded analytics.
- Design business‑friendly semantic layers, intuitive data models, and secure role‑based access.
- Build and maintain ETL/ELT pipelines: incremental loads, historical snapshots, SCD, validation, freshness monitoring, and alerting.
- Ensure low‑latency query performance, cost control, and predictable behavior in a multi‑tenant SaaS environment.
- Implement tenant isolation, row‑level security, and governance frameworks aligned with public‑sector expectations.
- Enable AI/ML requirements: feature extraction, labeled datasets, and future integration of forecasting, anomaly detection, and conversational insights.
- Collaborate with application engineers to embed dashboards, reports, and interactive analytics inside the product UI.
- Prioritize analytics features with product management and contribute to the long‑term data platform strategy.
- Document data models, metrics, and best practices for internal and external audiences.
Required Skills:
- 7+ years in data or analytics engineering.
- Advanced SQL and experience with modern cloud data warehouses.
- Python for data transformation and pipeline development.
- Expertise in multi‑tenant SaaS data design, performance tuning, and cost optimization.
- Knowledge of embedded analytics platforms, semantic layers, and data governance (RLS, tenant isolation).
- Familiarity with AI/ML data pipelines, feature stores, and time‑series analytics.
- Strong communication, documentation, and cross‑functional collaboration.
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Data Engineering, or related field (or equivalent experience).
- Certifications in relevant technologies (e.g., Snowflake, BigQuery, Redshift, Databricks) are a plus.