Senior Data Engineer at Benchmark Solutions LLC

Chicago, Illinois, United States -

Full Time

Start Date

Immediate

Expiry Date

10 Aug, 26

Salary

160000.0

Posted On

12 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, AWS, Kubernetes, Docker, ETL/ELT, Data Modeling, Airflow, Spark, Postgres, DynamoDB, CI/CD, IaC, NoSQL, Django, LLM Integration

Industry

Software Development

Description

Description Who We Are: Dedicated to making a difference in law enforcement agencies across the U.S., our mission is to transform policing by elevating officer performance with a preventative-based early intervention system. Driven by data science and powered by machine learning, our offering analyzes officer performance data in order to identify potentially problematic behavior. In partnership with the University of Chicago, we’ve developed the world’s largest multi-jurisdictional officer performance database, and the only research-driven, evidence-based early intervention system available in policing today. We’re also the only provider of a fully integrated, cloud-based Software-as-a-Service (SaaS) platform that simplifies essential policing workflows. This platform is designed to be a single-source solution for all operational needs, driving extensive efficiency gains and providing best-in-class advanced analytics and insights. Benchmark Analytics provides a comprehensive, all-in-one solution that is advancing police force management through state-of-the-art technology and market-leading data and analytics. The Role: We are actively evolving our data platform from legacy ETL systems to a modern, cloud-native architecture built on Python, Kubernetes, and AI-assisted and agentic workflows. This role will play a critical part in that transformation. Responsibilities: Designing, developing, and maintaining scalable, fault-tolerant data pipelines and ETL/ELT processes across a modern stack Contributing to the design and implementation of a greenfield data platform leveraging Python, Kubernetes, and AWS services Operating in a hybrid greenfield and brownfield environment: building new capabilities while maintaining legacy systems Leading development discussions and defining engineering patterns and standards Assessing and analyzing legacy data processes and driving modernization efforts Collaborating with cross-functional teams to ensure delivery of clean, reliable, and production-ready data Improving data pipeline performance, observability, and reliability Designing and integrating AI-assisted or agentic workflows to improve data processing and system interaction Supporting documentation efforts for scalability and platform adoption Providing technical mentorship and guidance to junior engineers Acting as a technical SME in internal and client-facing discussions Job Qualifications: Requirements Bachelor’s degree in STEM field or equivalent experience 6+ years of experience building production-grade data systems, with demonstrated ownership of system design or major platform components Strong experience building ETL/ELT pipelines across structured and unstructured data Experience with cloud-based architectures (AWS preferred) Strong SQL and data modeling skills Strong Python engineering skills Experience with Docker and orchestration frameworks (Airflow or equivalent) Experience modernizing or migrating legacy systems Proven ability to troubleshoot complex data issues Sufficient understanding of DevOps practices (CI/CD, IaC) Ability to manage multiple priorities in a fast-paced environment Required Skills Experience designing scalable data solutions in production Experience handling large data volumes and schema evolution Proficiency in SQL and relational/analytical databases Proficiency in Python (and/or Java, Shell) Experience with AWS ecosystem (S3, Lambda, SQS/SNS) Familiarity with Spark/EMR preferred Experience with Docker and Kubernetes Strong data modeling knowledge (relational and NoSQL) Technologies: SQL, Python, AWS, Postgres, Spark/EMR, Git, Docker, Kubernetes, Django, DynamoDB Preferred Qualifications Experience building or contributing to a greenfield data platform Experience migrating away from legacy ETL tools Experience integrating LLM or agent-based systems into data workflows (e.g., tool-calling, retrieval, automation) Experience working in regulated environments (e.g., GovCloud, HIPAA) What We Offer: A competitive salary and benefits package. Unlimited Paid Time Off. Ability to work in a fully remote environment (must be based in the U.S. and willing to work in Central Time Zone). Summer Half-Day Fridays. Freed-Up Fridays during Spring, Fall, and Winter months to promote productivity and dedicated heads-down work time. Medical, dental, and vision plan offerings along with 401(k). Employer-paid Short-Term Disability, Long-Term Disability, and Life Insurance. Other Voluntary Benefits include additional Life Insurance, Spouse Life Insurance, and Accident Insurance. The satisfaction that comes with being part of a solution that has real impact in the world. A diverse workforce and inclusive environment that embraces unique contributions and experiences. An empowered culture that encourages creativity and professional growth. Estimated Annual Salary Range: $135 - $160; based on role, experience, and location Additional Information: Benchmark Analytics is an Equal Opportunity Employer. We value diversity of all kinds in our effort to create a stellar workforce of committed and passionate team members. Unfortunately, we are not able to sponsor employment visas at this time, so we can only accept applications from candidates who are authorized to work in the U.S.

Responsibilities

Design and maintain scalable data pipelines and ETL/ELT processes while migrating legacy systems to a modern cloud-native architecture. Lead the implementation of a greenfield data platform using Python, Kubernetes, and AI-assisted workflows.