Data Engineer
Skills
Computer ScienceMicrosoft Azure Machine LearningSQLAmazon Web ServicesApache SparkAzure DatabricksData Modeling
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Must have or be willing to obtain Secret Clearance (this requires US Citizenship)
- Strong SQL skills
- Experience with Snowflake, Databricks, Spark SQL, PySpark, and Python
- Cloud experience: Azure, AWS, or GCP
- Develop and maintain ETL pipelines
- Database design and principles
- Data modeling, schema development, and data-centric documentation
- Experience integrating data from a variety of data source types
- Recommend and advise on optimal data models for data ingestion, integration, and visualization
- Experience improving code performance and query optimization
- Use Continuous Integration/Continuous Delivery (CI/CD) concepts to engineer a standardized data environment
- Outstanding problem-solving skills
- Excellent verbal and written communication skills and the ability to interact professionally with a diverse group, including executives, managers, and subject matter experts
Nice to have
- Experience with both structured and unstructured data
- Experience with ML software, like SciKit Learn, SparkML, TensorFlow, Horovod, and Petastorm
- Experience with Hadoop, Hive, and R
- Understand best practices for effective predictive models, including cluster management and algorithms
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or comparable academic discipline
Day to day
- As a Data Engineer, you will work hands-on with challenging data engineering, data management, and analytics projects.
- You will collaborate with data scientists, analysts, business users, and IT teams to design, implement, and deploy data services and analytics.
- We value passion, curiosity, and perseverance with an ability to communicate ideas and results to diverse audiences.
