Senior Data Engineer SQL
New
J
JobgetherData Engineering
United StatesFull-TimeSenior
Salary110,000 - 155,000 USD per year
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Job Details
- Experience
- 1+ years
- Required Skills
- AWSPostgreSQLPythonSQLKafkaAzureFastAPITerraformDatabricks
Requirements
- 1+ years of relevant industry experience in data engineering, analytics, data science, or a closely related discipline, or a Bachelor's/Master's degree in Engineering, Mathematics, Statistics, Computer Science, or another quantitative field.
- Strong hands-on SQL Server expertise, particularly T-SQL and query-intensive workloads, with an emphasis on direct SQL rather than ORM-based development.
- Working knowledge of PostgreSQL, including the ability to read data from replicated environments.
- Proficiency in Python and FastAPI for developing data-oriented applications and services.
- Experience with scikit-learn, including techniques such as percentile calculations and outlier detection.
- Understanding of acceptance and likelihood models, including carrier-acceptance-probability logic and related analytical approaches.
- Experience consuming data from Kafka, without necessarily requiring experience building Kafka infrastructure.
- Ability to read and understand C# code sufficiently to extract business and application logic.
- Familiarity with AWS services such as S3, RDS, Secrets Manager, and CloudWatch.
- Working knowledge of Terraform and the ability to confidently navigate infrastructure-as-code configurations.
Responsibilities
- Design, build, and support non-interactive batch, distributed, and real-time data pipelines that are highly available, accurate, and scalable.
- Develop fault-tolerant, self-healing, and adaptive data processing and computational pipelines.
- Apply deep data engineering expertise to complex technical programs, providing consultation and leading implementation efforts.
- Develop, maintain, and continuously improve documentation for assigned systems, data solutions, and projects.
- Optimize and tune SQL queries operating over billions of rows within distributed query environments.
- Perform root cause analysis on software and business-process issues and implement sustainable, permanent resolutions.
- Work across data engineering, analytics, and data science initiatives to translate technical requirements into reliable production solutions.
- Use automation, cloud services, and infrastructure-as-code practices to improve the reliability and maintainability of data platforms.
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