Data Engineer

BT-166 – Data Engineer

Location: McLean (fully on-site, no remote option)

Poly clearance required: Must have a Poly clearance to apply. Those who do not have a Poly clearance will not be considered.

Bespoke Technologies is seeking a Data Engineer who will provide highly technical and in-depth data engineering support.

• Must have experience with data engineering, to include designing and building data infrastructure, developing data pipelines, transforming and preparing data, ensuring data quality and security, and monitoring and optimizing systems.
• Must have extensive experience with Python and AWS.
• Experience with SQL, multi-data source queries with database technologies (Postgre
  
  SQL, MySQL, RDS, etc.), NiFi, Git, Elasticsearch, Kibana, Jupyter Notebooks, NLP, AI, and any data visualization tools (Tableau, Kibana, Qlik, etc.) desired.

• Demonstrated experience with data engineering, to include designing and building data infrastructure, developing data pipelines, transforming/preparing data, ensuring data quality and security, and monitoring/optimizing systems.
• Demonstrated experience with data management and integration, including designing and operating robust data layers for application development across local and cloud or web data sources.
• Demonstrated experience programming with Python.
• Demonstrated experience building scalable ETL and ELT workflows for reporting and analytics.
• Demonstrated experience with general Linux computing and advanced bash scripting.
• Demonstrated experience with SQL.
• Demonstrated experience constructing complex multi-data source queries with database technologies such as Postgre
  
  SQL, MySQL, Neo4J or RDS.
• Demonstrated experience processing data sources containing structured or unstructured data.
• Demonstrated experience developing data pipelines with NiFi to bring data into a central environment.
• Demonstrated experience delivering results to stakeholders through written documentation and oral briefings.
• Demonstrated experience using code repositories such as Git.
• Demonstrated experience using Elastic and Kibana technologies.
• Demonstrated experience working with multiple stakeholders.
• Demonstrated experience documenting artifacts such as code, Python packages, and methodologies.
• Demonstrated experience using Jupyter Notebooks.
• Demonstrated experience with machine learning techniques including natural language processing.
• Demonstrated experience explaining complex technical issues to more junior data scientists in graphical, verbal, or written formats.
• Demonstrated experience developing tested, reusable and reproducible work.
• Work or educational background in one or more of the following areas: mathematics, statistics, hard sciences (e.g., Physics, Computational Biology, Astronomy, Neuroscience, etc.), computer science, data science, or business analytics.

• Demonstrated experience with cloud services, such as AWS, as well as cloud data technologies and architecture.
• Demonstrated experience using big data processing tools such as Apache Spark or Trino.
• Demonstrated experience with machine learning algorithms.
• Demonstrated experience with using container frameworks such as Docker or Kubernetes.
• Demonstrated experience with using data visualization tools such as Tableau, Kibana, or Apache Superset.
• Demonstrated experience creating learning objectives and creating teaching curriculum in technical or scientific fields.