🛠 Tech Stack

💼 About This Role

You'll design and evolve advanced data architectures for large-scale analytics and AI. You'll build reusable frameworks and shape next-generation data ecosystems using modern cloud platforms.

🎯 What You'll Do

• Develop and optimize metadata-driven ETL/ELT pipelines for analytical structures.
• Design scalable data architectures using Data Mesh, Lakehouse, and Data Vault.
• Create reusable frameworks, accelerators, and engineering best practices.
• Implement emerging technologies like Apache Iceberg, Microsoft Fabric, and DLT.

📋 Requirements

• 7+ years as a Data Engineer building ingestion/transformation solutions.
• Expertise in Data Warehouse modeling (Kimball, Inmon, Data Vault 2.0).
• Hands-on experience with dbt, dlt, Apache Airflow, or Azure Data Factory.
• Experience with cloud data platforms like Snowflake, BigQuery, Databricks.

✨ Nice to Have

• Knowledge of DataOps, Data Observability, or Data Mesh concepts.
• Familiarity with AI/ML pipelines and MLOps environments.

🎁 Benefits & Perks

• 🏖️ Flexible work model with fully remote or hybrid options.
• 📚 Ongoing learning support including certifications and training.
• 💻 Financial support for remote work setup and home office needs.
• 🏢 Stable full-time position with strong career growth opportunities.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3System Design· 60 min