Research Analytics Engineer

The company name is \"The Philadelphia District Attorney’s Office\".; Chicago (IL); On-site; USD 115,000 - 145,000; Full time

Benefits offered by this job

Retirement benefits

PSLF program

Health coverage

Paid time off

Wellness program

Commuter benefits

FSAs

Job summary

The Philadelphia District Attorney’s Office, through the DATA Lab, seeks a Research Data Engineer to design and maintain automated data pipelines and deliver research-ready datasets for embedded researchers.

You will work with the Infrastructure and Penn teams to align data needs and improve reporting accuracy.

Qualifications

• Bachelor's degree in a relevant field; computer science or data-related preferred.
• 3+ years of experience in data engineering or research data workflows.
• Proficiency in Python and SQL; ability to explain concepts to non-technical partners.

Responsibilities

• Design, build, and maintain automated, scalable data pipelines.
• Create research-ready datasets and documentation for internal researchers.
• Ensure data quality, efficiency, and accuracy across pipelines.
• Triage issues, participate in Agile ceremonies, and collaborate with multiple teams.
• Assist in integrating new data sources and maintaining version control.

Skills

Python

SQL

AWS

Airflow

Linux

Git

Data pipelines

Communication

Education

BS in Computer Science / related field

Tools

Airflow

Docker

GitHub

AWS

Job description

Unit: District Attorney's Transparency Analytics (DATA) Lab

The Philadelphia District Attorney’s Office is the largest prosecutor’s office in Pennsylvania, and one of the largest in the nation. It serves more than 1.5 million citizens of the City and County of Philadelphia, employing 600 lawyers, detectives, and support staff. Our Assistant District Attorneys are dedicated to public service, public safety, and justice for all involved in the criminal justice system.

The Philadelphia District Attorney’s Office in particular is committed to several citywide collaborations aimed at reducing Philadelphia’s jail population and improving the criminal justice system overall.

**Please note that effective September 1, 2021, the City of Philadelphia requires all new employees to present proof of vaccination against COVID-19. **

To attain a job with the city, you must be a city of Philadelphia resident within 6 months (180 days) of hire and able to work completely in the office.

Summary of Job

The District Attorney’s Transparency Analytics (DATA) Lab is hiring its first Research Data Engineer to join our Infrastructure team, with a special focus on supporting embedded researchers and analysts from the Penn Prosecution Lab. The DATA Lab's mission is to use data, research, and advocacy to inform policies and practices; increase equity, transparency, and accountability; and reduce harm through prosecutorial and systems reform in Philadelphia and beyond. This unique position will work closely with our Infrastructure and Research teams and DATA Lab leadership to help align, prioritize, and solve the technical and data needs of our embedded research partners. By addressing issues infrastructurally, improvements will benefit all DATA Lab personnel and numerous partners. Responsibilities include building data pipelines that extract, transform, and load data into the DATA Lab's Postgres reporting database. The DATA Lab and Penn teams use data from the DAO, the courts, police, prisons, and other sources to inform day-to-day operations at the DAO, shape policy in the criminal legal space, support external research, and more. The technological landscape is continuously evolving, and we consistently iterate our data pipelines to provide accurate, timely data. Data pipelines are written in a combination of R and Python and feed into an AWS RDS database, using Airflow orchestration.

The Research Data Engineer will work closely with the Supervising Data Engineer, Penn team, project managers, unit leadership, data analysts, and other DAO staff. This position reports to the Supervising Data Engineer in the DATA Lab.

This is a grant-funded position for at least 2 years.

How You Will Make an Impact

• Be part of a nationally recognized team doing innovative research and analysis of the criminal legal system from within a prosecutor’s office.
• Open the doors of the office to community members and research partners by opening unprecedented prosecution data to the public through direct data sharing, public data releases, data stories, analyses, and DAO-sponsored studies.
• Harness volumes of criminal legal data from a wide array of sources, consolidate and connect it, and produce analytical and research-ready data and documentation.
• Work in an environment free of vibe coding and develop true hand-crafted, human-created work.

Job Responsibilities

• Serve as primary contact for database-related questions from Penn team (availability of a particular field or variable, how to access a database, troubleshooting server issues, etc.)
• Design, build, and maintain automated, scalable, and test-driven data pipelines.
• Build research-ready versions of datasets and documentation for Penn team and external researchers.
• Ensure quality, efficiency, and accuracy of data.
• Troubleshoot and fix errors and outages as they occur.Participate in Agile ceremonies, such as sprint planning, daily standup, and retro.
• Support DATA Lab Infra team in identifying and integrating new data sources.
• Manage version control for Penn research code and support Penn team researchers in best practices.
• Support DATA Lab reviews of Penn Fellows’ work to ensure proper interpretation of data, including leading code review process for replication packets.

Skills & Qualifications

• Education and/or experience: A background in computer science and academic research, or equivalent experience of at least 3 years, is desired. Prior experience working with researchers is preferred.
• Strong interpersonal and communication skills, with a collaborative and service-oriented approach to data work. Ability to explain technical concepts clearly and accessible to colleagues with varying levels of technical expertise. Proficiency in Python or a demonstrated ability to learn it.
• Proficiency in SQL
• Proficiency in R, statistics, and research methods. Familiarity with experimental and quasi-experimental methods is preferred
• A demonstrated ability to build ETL pipelines
• Be a team player who can communicate and collaborate with the Infrastructure, Penn Research, Analytics, and internal Research teams
• Familiarity with Git and GitHub for version control
• Familiarity with AWS
• Experience with Linux; Airflow is a plus

This is an exempt employee with the City of Philadelphia. Immediately upon assuming office, new hire will receive benefits similar to those of other City of Philadelphia employees, including the below benefits:

• Generous retirement savings options available (pension plan and etc.)
• We are a Public Service Loan Forgiveness (PSLF) Program qualified employer
• We offer comprehensive health coverage (medical, vision, prescription and dental) for employees and their eligible dependents
• Annual paid time off (PTO) package: 10 vacation days, 15 sick leave days, 11 paid holidays, 5 annual administrative leave
• Our wellness program offers eligibility into the discounted medical plan
• Before tax commuter program
• Health care and Dependent care flexible spending accounts
• Sick leave bonuses and exchanges
• Employee Assistance Program (EAP)

Applications will be active for one year from the date of receipt by the Office.

All exempt employees of the District Attorney’s Office are at-will employees and serve at the pleasure of the District Attorney. The at-will relationship shall not be modified for any employee and no agreement, oral or written, shall be entered into that changes the at-will relationship.

The Philadelphia District Attorney's Office is an Equal Opportunity Employer and does not discriminate on the basis of race, color, national origin, sexual orientation, gender identity, religion, national origin, ancestry, age, disability, marital status, source of income, familial status, genetic information or domestic or sexual violence victim status.