Senior Data Engineer

Senior Data Engineer (Professional Services)

Location: India (100% Remote) Experience: 4–6 Years Work Dynamics: High-Growth Startup | Global Teams | Flexible Hours

1. Role Summary

Technical lead for global enterprise data projects. High-velocity startup environment. Requires a builder who automates everything with AI. Direct client-facing engagement. Translates business problems into robust technical designs.

2. Tech Stack

- Orchestration: Apache Airflow (Expert: multi-tenant DAGs, SLAs, monitoring). - Data Platforms: Snowflake (Ingestion, performance tuning) & DuckDB (Local analytics/prototyping). - Coding: Advanced Python (ETL frameworks) & Expert SQL (Data modeling fundamentals). - AI Productivity: Proficiency with LLMs/Copilots for code, docs, and self-healing pipelines.

3. Key Responsibilities

- Design and ship end-to-end ELT/ETL pipelines for enterprise customers. - Automate SQL generation and data quality tasks using AI. - Lead technical workshops and present solution designs to US/EMEA stakeholders. - Develop reusable Python frameworks to adapt to varied customer landscapes. - Manage Agile delivery, sprint planning, and production "Hypercare" phases. - Create consulting assets like accelerators and best practice templates.

4. Required Skills

- 5–7 years in Data Engineering or Technical Consulting. - Deep knowledge of Snowflake, DuckDB, and Airflow orchestration. - Expertise in modern data modeling (Star Schema, Kimball). - Fluent English for presenting trade-offs to international clients. - Ability to troubleshoot and deliver results with ambiguous requirements.

5. Ideal Mindset & Personality

- AI-First: Ambitious enough to automate manual tasks immediately. - Global Flexibility: Willing to shift hours for US/EMEA team syncs. - Creative Laziness: Hates repetitive work; builds tools to avoid it. - Startup DNA: High ownership and ability to operate with partial information. - Execution Focused: Balances speed, quality, and client expectations seamlessly.