Senior Data Engineer

• Background & Leadership:
  • Advanced degree (Master’s or equivalent) in Computer Science, Engineering, or a related technical discipline.
  • 10+ years of progressive software/data engineering experience, demonstrating strong technical leadership and collaborative team-first mindset.
• Core Data Engineering & Platform Stack:
  • 5+ years of deep, hands-on expertise within the Databricks ecosystem, leveraging Python, Apache Spark, Delta Lake, and Delta Live Tables (DLT).
  • Proven track record architecting enterprise Big Data solutions across Data Warehouses, Data Lakes, and Lakehouse architectures.
  • Extensive experience engineering high-throughput, fault-tolerant pipelines handling massive datasets across both batch and real-time streaming workflows.
• System Design & Non-Functional Requirements (NFRs):
  • Strong architectural background with an emphasis on low-latency processing, high data availability, and horizontal scalability.
  • Solid database engineering skills across relational and cloud engines (SQL, PostgreSQL, Azure SQL, PL/SQL).
• Cloud, Automation & DevOps:
  • Deep familiarity with cloud platforms (preferably Azure) combined with strong Linux/Unix environments and shell scripting.
  • Production experience establishing robust CI/CD workflows and automated test suites using GitLab and industry-standard tools.
• Engineering Practices & Innovation:
  • Practical adoption of AI-assisted engineering tools throughout the modern SDLC to accelerate delivery.
  • Rapid prototyping mindset—ability to quickly validate PoCs and systematically harden them into production-grade systems following clean code principles.

,[] Requirements: Degree, Data engineering, Databricks, Python, Apache Spark, Delta Live Table, Big Data, Data warehouses, Data Lake, Cloud, SQL, PostgreSQL, Azure SQL, PL/SQL, CI/CD, GitLab, SDLC, Prototyping, Clean Code, Cloud platform, Azure, Linux, Unix Tools: Agile, Scrum.