Senior Data and Analytics Engineer (Hybrid)
Tasks
- Address technical debt and manage development cost
- Architect data systems for iterative delivery and future scaling
- Build and maintain scalable data pipelines and ELT workflows
- Collaborate with stakeholders on end to end data requirements
- Create documentation templates and processes for data problems
- Design and build data transformation layers
- Develop and maintain dbt models
- Ensure data quality and test dbt models
- Identify communicate and solve cross cutting technical issues
- Optimize reliability maintainability and scalability
- Own data modeling decisions including entities relationships and grain
- Plan data engineering needs for product launches
- Proactively improve client data infrastructure and analytics capabilities
Perks/Benefits
Skills/Tech-stack
AWS | Apache Airflow | Azure | Azure Data | Azure Data Factory | DBT | Data Factory | Data Quality | Data Warehousing | Databricks | Delta Lake | Dimensional Modeling | ELT | ETL | Entity Relationship Modeling | Entity relationship | Fivetran | Google Cloud | Kafka | MLOps | Python | Relationship Modeling | SQL | Semantic layer | Snowflake | Spark Streaming | Unity Catalog
Education
N/A
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