We are looking for an experienced
Data Engineer
to design, develop, and maintain scalable data pipelines on
Databricks
and cloud platforms. This role will work closely with analytics, product, and infrastructure teams to support enterprise data, reporting, and analytics initiatives.
Key Responsibilities
Develop and maintain ETL pipelines for centralized data platforms such as Delta Lake.
Build ingestion, transformation, validation, and loading processes.
Integrate data from databases, APIs, streaming platforms, log files, and external providers.
Design and optimize scalable data processing solutions.
Implement data governance, monitoring, and reliability standards.
Develop monitoring tools, alerts, and automated error-handling mechanisms.
Support SIT, UAT, data profiling, validation, and production deployment.
Collaborate with business, analytics, product, and infrastructure stakeholders to deliver data solutions.
Required Skills
✅ 3+ years of Data Engineering experience
✅ Strong experience with:
Databricks
PySpark
Spark SQL
Databricks Notebooks & Jobs
Data Modelling
Distributed Computing Architectures
SQL Performance Optimization
✅ Experience with:
Azure Data Platform
Azure Data Factory (ADF), Airflow, or similar orchestration tools
Batch and Real-Time Data Processing
Git, CI/CD, and DevOps practices
Scrum/Agile methodologies
✅ Knowledge of streaming technologies such as:
Apache Kafka
Apache Flink
AWS Kinesis
Preferred Certifications
Databricks Certified Data Engineer Associate
Databricks Certified Data Engineer Professional
Why Join
Opportunity to work on enterprise-scale cloud and data transformation projects.
Exposure to modern Azure and Databricks technologies.
Collaborative environment focused on data innovation and engineering excellence.