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Senior Data Engineer
Skills
Computer ScienceAmazon RedshiftData ArchitectureDatabasesGlueInterest RatesModeling
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Bachelor's or advanced degree in Computer Science Engineering Data Science or equivalent experience
- Strong proficiency in Python and SQL for data engineering workflows
- Proven experience designing and operating large-scale data pipelines and data platforms in production
- Hands-on experience with AWS data tools such as Redshift Lambda and Glue or equivalents
- Experience with data orchestration and ETL tools like Airflow Airbyte and dbt in production
- Experience implementing monitoring alerting and data quality frameworks
- Familiarity with streaming or near-real-time systems such as Kafka or Kinesis is a plus
- Hands-on experience with PostgreSQL and NoSQL databases like MongoDB or DynamoDB
- Experience supporting machine learning or AI workflows such as feature engineering embeddings or vector databases
- Strong collaboration and communication skills
- Experience with data governance security and compliance in regulated or sensitive-data environments
Nice to have
- Technical leadership
- Analytical mindset
- Reliability focus
- Cross-functional collaborator
- Detail oriented
- Process improvement
Day to day
- Lead the design and evolution of a scalable data platform that supports reliable and near-real-time use cases.
- Build and maintain production-grade batch and streaming pipelines with strong monitoring, alerting, and data quality controls.
- Partner with analysts, engineers, and product managers to deliver trusted data models, robust reporting, and data-enabled products.