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.