Lead Engineer/ Data Platform
Lead Data Engineer / Data Platform Engineer
Join a high-performing engineering team building a scalable, cloud-native data platform that powers enterprise analytics and data-driven decision-making. In this role, you'll design and deliver modern data solutions using AWS, Databricks, and Python while leading technical initiatives across distributed teams.
Key Responsibilities
- Design, build, and maintain scalable cloud-based data platforms and data pipelines.
- Develop high-performance data ingestion, ELT, streaming, and transformation solutions using Python, SQL, and Databricks.
- Design data lakes, warehouses, APIs, and access layers to support analytics and business applications.
- Provide technical leadership, define best practices, and mentor engineering teams.
- Collaborate with architects, product owners, and stakeholders to deliver high-quality data solutions.
- Drive cloud adoption, CI/CD, automation, and engineering excellence.
Requirements
- 6+ years of experience in Data Engineering or Software Engineering.
- Strong Python and SQL programming skills.
- Hands-on experience with Databricks, PySpark, Delta Lake, and Spark Streaming.
- Experience building scalable data platforms on AWS.
- Knowledge of data architecture, data modelling, and distributed systems.
- Experience with Kubernetes, MongoDB, Airflow, dbt, Git, and CI/CD is advantageous.
- Excellent communication and stakeholder management skills.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline.
Preferred Skills
- Cloud-native architecture and microservices.
- Event-driven systems and real-time data processing.
- Experience working in agile, fast-paced engineering environments.