[1 year contract, renewable]
As a Data Engineer in the Government Productivity Engineering (GPE) Group, you will play a crucial role in designing, building, and maintaining scalable data pipelines and infrastructure. You will collaborate with various teams to deliver data-driven solutions that support government productivity initiatives, ensuring data integrity and accessibility.
Key Responsibilities:
· Perform data extraction, cleaning, transformation, and loading (ETL/ELT).
· Design, build, and maintain batch and real-time data pipelines using modern frameworks.
· Integrate and consolidate data from multiple silos, ensuring scalability and compliance.
· Collaborate with Project Managers, Frontend Developers, UX Designers, and Data Analysts.
· Develop backend APIs and manage databases to support applications.
· Bridge the gap between engineering and analytics for data quality and availability.
· Work in an Agile environment with Continuous Integration and Delivery (CI/CD) practices.
· Participate in pair programming and code review processes.
Qualifications:
· Minimum of 4 years of professional experience in data engineering.
· Proven experience in building production-grade data pipelines with proper documentation.
· Proficiency in data cleaning and transformation (Pandas, PySpark, SQL).
· Strong knowledge of database design (PostgreSQL, MySQL, MongoDB).
· Understanding of system design, data structures, and algorithms.
· Familiarity with RESTful APIs and web protocols.
· Proficiency in at least two scripting languages (e.g., Python, SQL).
· Experience working in Windows and Linux environments.
· Hands-on experience with cloud platforms (AWS, Azure, Google Cloud).
· Knowledge of data modeling, Data Lakes, Data Marts, and Data Warehouses.
Preferred Skills:
· Proficiency in creating data dictionaries for consistent data definitions.
· Ability to design Entity-Relationship Diagrams (ERDs) to represent data models.
· Experience collaborating with stakeholders for business process understanding.
· Familiarity with BI tools like Tableau for data visualization.
· Experience with Docker containers.
