Job Board Title:
Environmental Data Specialist

Post Date
8/20/2024

Expiration Date
11/18/2024

Details:
Founded in 1981, AKRF is an award-winning consulting firm with 400 professionals bringing the value of strategic thinking to our land development, transportation, energy, and water clients. We serve our clients through a commitment to technical excellence across our portfolio of professional services, while always acting with integrity and fostering a culture of innovation, collaboration, and environmental stewardship. Offices are located throughout New York, New Jersey, Connecticut, Pennsylvania, Maryland, and Virginia, and the company completes projects around the country.


Professionals join and remain at AKRF for our corporate-casual environment that values flexible work schedules and locations, and balances award-winning planning, engineering, and environmental projects with social impact initiatives, charitable giving, and plenty of fun and games. Our firm fosters a diverse, equitable, and inclusive environment where employees are respected and valued in honor of their identities; we strive to deliver on this promise every day.


The Environmental Data Specialist position will provide in-house support to the Philadelphia Water Department’s (PWD’s) Green Stormwater Infrastructure (GSI) Monitoring, Analysis, and Research Support (MARS) group within the Office of Watersheds (OOW). The OOW is part of the Planning and Environmental Services Division of PWD. A watershed management planning process led to the decision to take the green approach to managing the City’s Combined Sewer Overflows (CSOs). This has evolved into one of the largest green stormwater infrastructure (GSI) programs in the country, known as Green City, Clean Waters.

Job Responsibilities:

Develop, document, and maintain the PostgreSQL database and scripting infrastructure used to store GSI monitoring data, fieldwork recordkeeping, and associated datasets necessary for GSI performance analysis.
Write, update, and maintain a library of R scripts used for calculating GSI performance metrics.
Maintain and modify systems of automated scripts that move data between locations (ETL).
Create, modify, and maintain R Shiny web applications to support the fieldwork team as their responsibilities evolve overtime.
Train new hires and co-ops in databases, R, and scripting.
Program in R and SQL, with occasional forays into Python or Windows batch files.
Perform data analysis leveraging the available data in PWD databases including water level data, GIS data, SMP design metrics, etc. to inform the decision-making process within the group such as identifying monitoring candidates.
Prepare and present written reports for technical and non-technical audiences, including OOW colleagues, peer groups within PWD, PWD executives, and regulatory bodies.
Think critically about the long-term sustainability of technology projects, ensuring that future users and maintainers of their work are set up for success.
Take initiative in identifying areas within MARS workflows which can benefit from automation.
Take ownership of data products including web apps, ETL scripts, etc. and be proactive with identifying areas to improve data integrity, accuracy, and overall efficiency.
Communicate with the team members routinely to identify their data analysis and automation needs, receive feedback, and train them in the use of new software products.

Qualifications:
Required:

1 plus years of experience coding using R, Python, SQL or similar.
1 plus years of experience in data analysis, database administration, or software development.
Degree in engineering, environmental science, computer science, data analytics, data science or similar technical degree.
Ability to write and optimize SQL queries and knowledge databases such as PostgreSQL, Microsoft SQL Server, or similar.
Strong proficiency in R programming (shiny, rmarkdown, ggplot2, tidyverse, etc), including data manipulation, statistical analysis, and data visualization. Alternatively, experience in Python (django, matplotlib, NumPy, pandas, etc) or similar languages may be considered.


Preferred:

1 plus years of work experience in water resources, stormwater, environmental science or similar fields.
Experience building R Shiny applications
Knowledge of software development methodologies such as agile, and best practices.
Proficiency in user interface (UI) and user experience (UX)principles.
Proficiency in using RStudio and Version Control software (Git).
Familiarity with POSIT Workbench, Connect, and/or PackageManager.
Familiarity with ArcGIS and geospatial data processing.


Comments:
What AKRF is offering:

We provide employees with a benefit package that reflects our respect for your workplace contributions, professional goals, and personal priorities. The benefits program at AKRF includes:
Medical, Dental, Vision insurance
Vacation and Sick time
Flexible and hybrid work schedules and locations
401(k) retirement plan with employer matching
Additional Voluntary Life Insurance
Short- and Long-Term Disability
Tuition Reimbursement
Training and professional development courses
Opportunities for community outreach through internal networks
Charitable donation match
Transit/parking program


Compensation will be commensurate with experience.


AKRF enforces a policy of equal employment opportunity in our daily operations. The firm has a demonstrated history of hiring, training, developing, promoting and retaining minority group members and women. All employment-related decisions are based solely on relevant criteria and without regard to race, color, religion, age, sex, pregnancy, national origin, age, physical or mental disability, marital status, sexual orientation, sexual identity, caregiver status, military/veteran status or citizenship status, or any other characteristic protected by federal, state, or local law.

Employer:
AKRF, Inc.
Contact:
Brian Cruice

Address:
530 Walnut St. Suite 998
Philadelphia, Pa 19106

Work Phone:
4846802277

Email:
bcruice@akrf.com

Website:
https://www.linkedin.com/jobs/view/4004600613/

Position Title:
Professional I