Key skills
AWSAzureNoSQLPySparkSparkSQLVaultData LakeDatabricksLambdaS3SQSGlueAthenaGit
About this role
Role Overview
- Develop, test, and maintain data pipelines in Databricks (Spark, PySpark, Delta Lake)
- Design and optimize analytical data models (dimensional, Data Vault, bronze/silver/gold layers)
- Participate in the implementation of solutions using Azure data services (ADF, Data Lake, Synapse, Databricks)
- Support data integration from multiple sources (SQL/NoSQL databases, APIs, streams)
- Write clean, version-controlled, and documented code (Git)
- Collaborate with engineering, product, and data science teams to ensure delivery quality
- Monitor pipelines, investigate incidents, and support continuous improvements
- Contribute to DataOps best practices, data governance, and observability
- Learn and participate in projects involving AWS (Glue, S3, Athena, EMR) as needed.
Requirements
- Bachelor's degree in Statistics, Computer Science, Engineering, or a related field
- More than 1 year of experience in data analysis
- Knowledge of Databricks
- Knowledge of Spark, PySpark, and Delta Lake
- Knowledge of AWS: S3, EMR, SQS, Lambda
- Proficiency in SQL or similar query languages for database querying.
Tech Stack
- AWS
- Azure
- NoSQL
- PySpark
- Spark
- SQL
- Vault
Benefits
- Health insurance
- Wellness program
- Professional development
- Flexible working hours
- Career opportunities