Data Engineer, Palo Alto

Rhombus•Palo Alto, CA

About The Position

Rhombus’ Data Engineers are instrumental in designing and implementing data engineering activities on topical, mission-driven projects that inform our national security agenda. They analyze, build, and maintain our organization’s data infrastructure and processing systems. Additionally, our Data Engineers perform various code development and query needs for integration with new and existing applications, dashboards and machine learning pipelines. Our Data Engineers work cross functionally with other departments to meet business needs. They utilize their skills at all stages of the analytics pipeline to create results that drive business values and customer success.

Requirements

At minimum Bachelor’s degree in Data Analytics, Computer Science, Computer Engineering, Information Systems/Sciences, or other relevant area (or equivalent experience) and at least 3 years of professional experience, or a Master’s degree with strong academic project experience and one year of work experience.
Experience with 1 or more programming and scripting languages, with a strong focus on Python, Pandas and Numpy. Other languages include: Shell, PERL, Java, C/C++/C#, Scala, etc.
Experience with 1 or more of the following relational, noSQL and/or file based storage (e.g. MYSQL, MongoDB, SQL Server, Oracle, Postgres, Hbase, DynamoDB, etc.)
Experience building and maintaining ETL data pipelines
Experience with software development life cycle including testing, documenting, delivery and support
Working knowledge of AWS/cloud technologies
Experience using query optimization as well as data modeling techniques.
Familiarity with machine learning frameworks (such as TensorFlow, Scikit-Learn, etc.)
Must have strong problem-solving skills and demonstrated excellent oral and written communication skills.

Responsibilities

Develop code using various programming and scripting languages to automate data ingestion and improve data management processes.
Architect data repositories, stand up data platforms and develop data pipelines for ingestion, transformation, and aggregation.
Review existing architecture, data strategy, and improve processes for data governance, data quality, and metadata management.
Extract and analyze raw data from multiple data sources via APIs, SQL Stored Procedures, or Python scripts.
Ability to develop scripts and programs for converting various types of data into usable formats and support project team to scale, monitor and operate data platforms.
Collaborate with a multi-disciplinary team of analysts, data scientists, data engineers, developers, and data consumers in a fast-paced, agile environment.
You’ll use your experience in analytical exploration and data examination while you manage the assessment, design, building, and maintenance of scalable platforms for clients.
Communicate project status and results to various levels of leadership.