TL;DR

Lead Data Engineer (Python, Snowflake, AWS): Leading the design, development, and delivery of scalable data solutions and data warehousing initiatives with an accent on architectural strategy, performance, and reliability. Focus on designing and implementing complex data models, building cloud-based data solutions, and optimizing data pipelines.

Location: Remote

Company

%hirify_global% is a global digital engineering and modernization partner, offering services across product engineering, cloud, quality, DevSecOps, data, cybersecurity, and AI.

What you will do

Lead end-to-end data platform and data warehousing initiatives, ensuring scalability and reliability.
Act as a hands-on technical lead, contributing to the design and optimization of data solutions.
Design and implement data models (including Data Vault) aligned with business requirements.
Build and maintain cloud-based data solutions using AWS and Snowflake.
Develop and optimize SQL and Python pipelines for data ingestion and analytics.
Collaborate with business and IT teams to translate needs into technical solutions and contribute to data strategy.

Requirements

3+ years of experience in Data Engineering / Data Warehousing.
Strong Data & Cloud background, with hands-on experience in Azure.
Extensive experience with Snowflake (architecture, performance tuning, cost optimization).
Strong experience in SQL and Python.
Solid experience in Data Modeling, including Data Vault.
Proven experience leading or acting as a technical lead on data projects.
Excellent communication and stakeholder management skills.

Culture & Benefits

Collaborative role between IT and business teams.
Focus on best practices and high-quality deliverables.
Proactive identification of process improvements and architectural enhancements.
Global team with over 9,000 experts in 47+ offices worldwide.
Commitment to non-discrimination and diversity in hiring.