Data Engineer
Tasks
- Apply AI ML concepts to automate data workflows
- Apply privacy controls for PII masking and tokenization
- Collaborate with clients to share progress and recommendations
- Create BI ready datasets for reporting and dashboards
- Define transformation logic and ensure data quality
- Design and build scalable data pipelines
- Develop cloud-native data solutions
- Implement data models and governance practices
- Ingest transform and prepare data for analytics and AI
- Set up CI/CD pipelines
- Support AI use cases with curated data
- Translate requirements into technical designs
- Use version control and unit testing for maintainable code
Perks/Benefits
Skills/Tech-stack
AI machine learning | AWS | Amazon Redshift | Azure | Azure Synapse | Azure Synapse Analytics | CI/CD | Data Governance | Data Quality | Data Warehousing | Databricks | Databricks SQL | Dimensional Modeling | GCP | Git | Google BigQuery | Logical models | Machine Learning | PII masking | Python | SQL | Snowflake | Source-to-Target Mapping | Synapse Analytics | Target Mapping | Tokenization | Unit Testing
Education
Roles
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