Data Engineer
Tasks
- Build data ingestion frameworks from databases APIs flat files and streaming sources
- Design and develop scalable ETL/ELT pipelines
- Develop curated datasets for reporting and advanced analytics
- Implement automated data quality checks and monitoring
- Integrate pipelines with cloud data lakes and data warehouses
- Maintain technical documentation and version control
- Optimize Spark application performance
- Optimize Spark jobs using DataFrames RDDs and Spark SQL
- Orchestrate data pipelines with Airflow or Oozie
- Participate in code reviews, testing, and CI/CD
- Troubleshoot pipeline failures and production issues
Perks/Benefits
- Career progression
- Comprehensive benefits plan
- Flexible workplace
- Referral bonus opportunity
- Successful referral program
Skills/Tech-stack
Airflow | Amazon Redshift | Amazon S3 | Apache Kafka | Apache Spark | Broadcast joins | CI/CD | Caching | Data Modeling | Data Quality | Data Validation | Data Warehousing | Dataframes | Delta Lake | ELT | ETL | Git | HDFS | Monitoring | Oozie | Partitioning | Performance Tuning | PySpark | Python | RDD | SQL | Snowflake | Spark SQL | Spark Structured Streaming | Structured Streaming | Version control | Workflow Orchestration
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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