The ideal candidate will have strong Python skills and experience building, maintaining, troubleshooting, and optimizing data pipelines. Experience with Apache NiFi is highly preferred, but candidates with other enterprise ETL platforms are welcome.
Responsibilities:
- Build and maintain data ingestion and ETL pipelines
- Create new data flows and enhance existing pipelines
- Consume data from Kafka and load/process it into MongoDB
- Write and modify Splunk queries for monitoring and analysis
- Perform data validation and data quality checks
- Troubleshoot pipeline failures and performance issues
- Refine and optimize existing pipelines
- Support operational issues and production incidents
- Occasionally assist with SQL development, table creation, and data investigations as needed
Requirements
- To be considered for this position, candidates must have experience in a similar role, or they must possess significant knowledge, experience, and abilities to successfully perform the responsibilities listed
- Relevant education and/or training will be considered a plus
- Experience moving and transforming large volumes of data
- Ability to learn and support Splunk
Experience with:
- Python
- ETL/Data Pipeline Development
- Kafka
- Data Validation/Data Quality
- Troubleshooting production data pipelines
Preferred Skills:
- Apache NiFi (strong preference)
- Splunk queries, monitoring, and troubleshooting
- MongoDB
- SQL
- Data flow design and optimization
- Streaming/data ingestion architectures
Nice-to-Have:
- Experience with Apache NiFi
- Telecom or large enterprise data environments
- Experience with real-time or streaming data architectures
- Exposure to Hadoop, Spark, or other big data platforms
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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