Overview
Skills
Job Details
|
| Data Engineer (Onsite) |
| Location: | Detroit, MI |
| Duration: | 12 Months |
| Pay Rate: | $55/hr on C2C / 1099 all inclusive (OR) $50/hr on W2 |
| Note | Interviews: Candidates MUST be available for the possibility of either in-person or virtual interviews. For virtual interviews please use a laptop and be prepared so share screen if asked. Use of headphones is strongly discouraged. A screenshot photo of candidate will be required for any Teams interviews as well as a vendor present at beginning of interview to validate candidate. This person will be working ONSITE in a full-time capacity in Detroit, MI. Remote work is not an option. Candidates must be currently local to the Detroit area in order to be considered.
|
| Job Description | Top Skills: A bachelor's or master's degree in computer science or a related technical field, and/or equivalent experience More than 3 years' experience transforming raw data into useful data systems/platforms Experience building and operating distributed systems of data extraction, ingestion, and processing of large data sets from multiple sources Expert command of SQL with experience building database tables Expert command of Python or similar analytical programming languages Experience compiling and maintaining technical documentation Experience communicating business requirements and project plans with internal clients
Responsibilities include the following: Contribute to the development of a modern data infrastructure that drives decision-making at all levels of the organization. Develop and maintain scalable data pipelines and build out new integrations to support the increasing data volume and complexity. Extract, transform, and load data from raw unstructured data to consumable structured data. Implement processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it. Write and curate documentation internally and externally around business rules for metrics. Collaborate as a contributing member of the Data Services Infrastructure working group.
Key projects include the following: Develop data pipelines to ingest and load data from various sources Implement automated data quality checks and alerts Contribute to the development and planning of calculating school performance metrics Maintain a vendor data sync that helps school-based staff access student data Optimize data infrastructure to enable analysts across the district to access core data |