Databricks Engineer
2 days ago
Description :
We are a technology consulting firm operating in Cloud Data Engineering and Analytics, helping enterprise customers build reliable, scalable data platforms and analytics products.
    Our teams deliver end-to-end data lakes, real-time streaming pipelines, and production-grade ML feature stores using Databricks and modern cloud data tooling.
Role & Responsibilities :
- Develop and optimize Spark/PySpark jobs for performance, cost-efficiency, and reliability; tune cluster sizing and autoscaling policies.
- Implement data quality, observability, lineage and monitoring (alerts, dashboards, job health) to ensure production SLAs.
- Collaborate with Data Engineers, Data Scientists and Architects to define schemas, partitioning strategies and data models that support analytics and ML use cases.
- Build CI/CD and release automation for Databricks assets (notebooks, jobs, Delta tables); manage Git-based source control and code review processes.
- Provide production support: troubleshoot job failures, perform root-cause analysis, and produce runbooks and post-incident improvement plans.
Skills & Qualifications :
- Delta Live Tables (DLT).
- Apache Spark.
- PySpark.
- Delta Lake.
- SQL.
Preferred :
- Azure Data Factory.
- Git / CI-CD tooling (Azure DevOps, GitHub Actions, Jenkins).
Additional Qualifications :
- Minimum 5 years of professional data engineering experience with hands-on Databricks development; strong understanding of cloud data platforms (Azure/AWS/GCP) and best practices for data governance, security, and cost optimisation.
    - Degree in Computer Science, Engineering, or equivalent practical experience is desirable.
Benefits & Culture Highlights :
- Opportunities to work on multi-enterprise data platform projects, upskill on Databricks and cloud services, and attend technical training.
- Collaborative teams, mentorship from senior engineers, and exposure to cloud architecture and ML productionisation.
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