Databricks Data Engineer

About the role

We are looking for a Databricks Data Engineer to design, develop and maintain scalable data solutions. You will build end‑to‑end pipelines, ensure data quality, and support advanced analytics across cloud environments.

Key responsibilities

• Develop high‑performance ETL/ELT pipelines using Databricks technologies such as Delta Lake, Auto Loader and Delta Live Tables.
• Write production‑grade Python and PySpark code for data transformation, validation and PII masking.
• Configure Unity Catalog, manage access controls, audit logging and data masking for secure data sharing.
• Integrate BI tools (Power BI, Tableau, Looker) with Databricks via optimized connectors and build stakeholder dashboards.
• Prepare GenAI‑ready datasets, manage vector embeddings and use Feature Store with MLflow.
• Package and deploy pipelines through CI/CD pipelines in GitHub or GitLab, leveraging dbx and Asset Bundles.
• Troubleshoot, tune and optimise jobs using Photon engine and serverless compute to meet cost and SLA targets.

Required profile

• Minimum 2 years of experience in cloud‑based data engineering, data warehousing and real‑time streaming.
• Strong understanding of data modelling, performance optimisation and data‑quality best practices.
• Hands‑on experience with at least one cloud platform (AWS, GCP or Azure).
• Relevant certifications (e.g., Databricks Certified Professional) are a plus.

Required skills

• Python
• PySpark
• Databricks, Delta Lake, Auto Loader, Delta Live Tables
• Unity Catalog
• AWS, GCP or Azure
• SQL
• Power BI, Tableau, Looker
• GitHub, GitLab, CI/CD
• Photon engine, serverless compute
• Vector Search, MLflow
• Apache Airflow
• Hadoop, Hive, Kafka
• Informatica, Talend, Matillion, Fivetran
• dbt

What we offer

• Competitive compensation with performance bonus and 13th‑month pay.
• Day‑1 health insurance (HMO) and life‑insurance coverage.
• Opportunities for professional growth and certifications.