Website:
nexabits.com
Job details:
A product-oriented Data Engineer with 2–3 years of experience building end-to-end data platforms on modern lakehouse and warehouse technologies, primarily Databricks, to help startups and scale-ups move from raw data to reliable, actionable insights
Core Tech Stack
- Databricks: Spark/PySpark, Spark SQL, Delta Lake, Databricks SQL, Jobs, Workflows, Unity Catalog
- Orchestration & ELT: REST API integrations, batch and near real-time pipelines
- Data Modeling & Architecture: Lakehouse patterns on object storage, dimensional modeling for analytics, medallion architecture
- Analytics: Serving curated data to BI tools (e.g., Power BI, Tableau, Looker) and supporting analysts and data scientists
- Engineering Practices: Git-based workflows, CI/CD for data pipelines, testing, monitoring, and basic observability
How I Help Startups & Scale-Ups
- Set up lean but scalable Databricks centric data stacks that keep complexity and costs low while the business grows
- Build robust ingestion and transformation pipelines from product databases, SaaS tools, and event streams into well-modeled tables for self-service analytics
- Implement data quality checks, documentation, and governance-lite (roles, permissions, catalogs) to keep data trustworthy as teams and use cases expand.
- Partner with department, functions and growth teams to quickly turn key metrics, funnel logic, and experiment data into reusable, production-grade datasets
Ideal Role
Owning the end-to-end modern data stack around Databricks, and acting as the bridge between engineering and business to make data a real growth lever for young, fast-moving companies.
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