Lead Data Engineer

Role & responsibilities

modern data architectures

• Develop and optimize data pipelines and ETL/ELT processes for high-volume, high-velocity data.
• Lead data platform modernization initiatives using cutting-edge tools and frameworks.
• Define and enforce data governance, security, and compliance standards.
• Partner with Data Science, BI, and Product teams to ensure data availability, accuracy, and performance.
• Provide technical leadership and mentorship to data engineers and developers.
• Implement DevOps/Data Ops practices for automated testing, deployment, and monitoring.
• Continuously evaluate and introduce innovative data technologies that enhance efficiency and scalability.
• Translate business requirements into robust and scalable technical data solutions.
• Support real-time and streaming data architectures for analytics and ML workloads.
• Designing and developing REST APIs / Azure App Services and implementing Azure PaaS solutions.

Preferred candidate profile

• Bachelors or master’s in computer science, Engineering, or related field.
• 10+ years in Data Engineering or Data Architecture roles.
• Expertise in

  Python, SQL, Spark, Kafka, and Airflow

  .
• Proven experience with

  cloud platforms

  (AWS, Azure, or GCP).
• Hands-on experience with

  Snowflake, Databricks, or Delta Lake

  .
• Strong understanding of

  data modelling, governance, and lineage tools

  .
• Excellent

  problem-solving, leadership,

  and

  communication skills

  .

Good to Have Skills:

• C#, .NET Core, Azure PaaS, Problem-Solving, REST API Development, EF Core, Leadership, Agile Practices.
• Blazor UI, Azure IPaaS (Azure Integration Services), Design Patterns, and Cloud Security best practices.