Data Engineer I - Remote, US

Bowman
United States
Category
Surveyor
Job Description
Purpose

The Data Engineer is crucial in developing and deploying innovative data systems such as automated extract, transform, load (ETL) tools, spatial data ETL, and RESTful services. The engineer will work with various technologies, including, but not limited to, the FME Platform, Python, SQL, APIs, and databases, to build robust data pipelines and platforms, ensuring the seamless flow and accessibility of data across the organizations.

Key Responsibilities

Leadership and Direction
  • Receive general instruction on key objectives for execution. Receive direction as needed, and especially complex assignments, modified techniques, and new approaches on assignments with conflicting criteria. Work is completed using advanced techniques and principles and is reviewed by more senior staff to ensure application of sound professional judgement. May review work produced by junior staff for quality assurance.

At the Operational and Company Level
  • Collaborate with data scientists, analysts, clients, agencies, and subcontractors to enhance interconnectivity and leverage data to drive business decisions and strategies.

Do the Work
  • Source data from across the organization and external parties as needed, ensuring data integrity and consistency.
  • Utilize various methods to collect data from diverse sources.
  • Process, clean, and document processes and data sources to ensure clarity and transparency.
  • Use programmatic methods (Python, SQL, Java, or similar) to interpret and improve data, develop automated ETL tools, and work with RESTful services and APIs.
  • Handle spatial data ETL and work with the FME platform to optimize data extraction and transformation processes.
  • Analyze trends and develop interactive tools for data visualization and presentation.
  • Develop standard operating procedures ("SOP") for ETL pipelines to ensure efficient replication and updates.
  • Organize and prepare data for deliverables, presentations, and decision-making.
  • Develop predictive models to drive business insights and actions using machine learning techniques.
  • Create impactful visualizations of data with appropriate tools.

Success Metrics and Competencies

Ideal candidate will consistently demonstrate...
  • High level of motivation, a problem-solving attitude, and a strong sense of urgency in responding to stakeholders.
  • Ability to effectively manage multiple time-sensitive tasks.
  • Strong work ethic, commitment to quality, and attention to detail.
  • Effective verbal and written communication skills.
  • Self-reliance and the ability to operate independently with limited direction.
  • Aspiration to grow professionally and advance within the company.
  • Ability to work effectively with internal leaders, peers, and external clients.
  • Commitment to promoting the company's reputation through quality of work.
  • Data analysis and interpretation skills and translating data into actionable insights.

Education, Work Experience, Licensure/Certifications, and Technical Requirements
  • Bachelor's degree in Technology, Computer Science, Engineering, advanced math, or Management Information Systems preferred or commensurate coursework in related field.
  • Additional experience may be considered as a substitution for the education requirement.
  • Entry level position, no prior experience required. Any data manipulation experience a plus.
  • Experience with data science, data modeling, machine learning, and operations research.
  • Proficiency in Python and SQL and familiarity with additional languages such as R.
  • Experience in database design, modeling, and administration, with skills in creating and managing ETL pipelines, optimizing database performance, and ensuring data security.
  • Experience with the FME platform, RESTful services, APIs, and spatial data ETL.
  • Experience using data visualization tools (interactive mappings such as ArcGIS Online and Enterprise).
  • Strong problem-solving abilities and adaptive reasoning skills.
  • Relevant Computer Science, Engineering, or equivalent experience in the Data Science field.
  • Graduate degrees or coursework focusing on Data Science or Machine Learning preferred.

Physical Demands and Working Environment
  • May be eligible for remote or hybrid work arrangements.
  • Primarily indoor professional office environment, which can consist of possible bright/dim light, noise, fumes, odors, and traffic.
  • Mobility around an office environment, occasional squat or kneel.
  • Mobility around a job/construction site to include walking, bending, crawling, climbing, squatting, or kneeling and wearing of required Personal Protective Equipment (PPE).
  • Frequent and prolonged use of standard office equipment such as computers, phones, photocopiers, filing cabinets and fax machines.
  • Occasional lifting or carrying up to 20 pounds.
  • Occasional pushing or pulling up to 20 pounds.
  • Occasional reaching outward or above shoulder.

Note: While this job description is intended to be an accurate reflection of the job requirements, it is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Management reserves the right to modify, add, or remove duties from particular jobs and to assign other duties as necessary at any time with or without notice.

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Employer
Bowman