Data Engineer

Jobot; Chicago (IL); On-site; USD 180,000 - 250,000; Full time

Job summary

Jobot is seeking a Lead Data Engineer in Chicago, IL to own design and expansion of our data platform, driving batch and streaming pipelines across hybrid cloud using Kubernetes, Kafka, and Databricks. You will mentor engineers, deliver high-quality code, and ensure data quality and SLAs in a fast-paced, Agile environment.

Requirements include 5+ years in software/data engineering, Java/Scala, Python, and hands-on AWS cloud experience; familiarity with Delta Lake, Spark, Kubernetes, and data

Qualifications

• BS/MS/PhD in Computer Science or equivalent technical field.
• 5+ years of professional software/data engineering experience.
• Proficiency in Java/Scala; Python is a plus.
• Experience with data platforms and technologies like Delta Lake, Spark, Kubernetes, Kafka, Databricks.
• Experience building large-scale batch and streaming pipelines with SLA and data quality requirements.
• Strong communication, analytical and problem-solving skills.

Responsibilities

• Build and deploy batch and streaming pipelines across a hybrid cloud architecture using Kubernetes/EKS, Kafka/MSK, and Databricks/Spark.
• Mentor junior engineers in software and data engineering best practices.
• Produce clean, well-tested, documented code for mission-critical applications.
• Create automated data validation test suites to enforce data quality and SLA commitments.
• Collaborate with Trading, Quant, Technology, and Business Operations to define data production/consumption workflows.

Skills

Java/Scala

Python

Data engineering

Batch & streaming

Education

BS/MS/PhD in CS/Engineering/Math

Tools

Kubernetes

Kafka/MSK

Databricks

Spark

Delta Lake

ClickHouse

Presto/Trino

AWS Cloud

Job description

Lead Data Engineer | 5+ Years Experience | Scalable Batch & Streaming Pipelines | Cloud Architecture (AWS, Databricks, Kubernetes)

This Jobot Job is hosted by: Jim Quirk

Salary: $180,000 - $250,000 per year

A bit about us

We are a fast-growing, tech-driven firm operating in a fast-paced market environment where data is central to our competitive edge. Our technology organization values high-performance engineering, hybrid-cloud scalability, and rigorous data quality. We foster a collaborative, Agile culture where engineers enjoy deep technical ownership, mentor peers, and directly impact mission-critical operation

Why join us

Drive High-Impact Innovation: You will have full ownership of the architecture, pushing our data platform beyond current tech limits to support rapid business growth.

Job Details

In this role, you will: Work within a growing Data Engineering division supporting the strategic role of data at the firm. Drive the ongoing design and expansion of our data platform across a wide variety of data sources, supporting an array of streaming, operational, and research workflows. Work closely with Trading, Quant, Technology, and Business Operations teams throughout the firm to identify how data is produced and consumed, helping to define and deliver high-impact projects. Build and deploy batch and streaming pipelines to collect and transform our rapidly growing Big Data set within our hybrid cloud architecture utilizing Kubernetes/EKS, Kafka/MSK, and Databricks/Spark. Mentor junior engineers in software and data engineering best practices. Produce clean, well-tested, and documented code with a clear design to support mission-critical applications. Build automated data validation test suites that ensure that data is processed and published in accordance with well-defined Service Level Agreements (SLAs) pertaining to data quality, data availability, and data correctness. Challenge the status quo and help push our organization forward as we grow beyond the limits of our current tech stack. Qualities that make great candidates: BS/MS/PhD in Computer Science, Engineering, Physics, Math, or equivalent technical field. 5+ years of professional experience developing software applications. Java/Scala experience required; Python experience is a significant plus. Highly motivated and willing to take ownership of high-impact projects upon arrival. Prior hands-on experience with data platforms and technologies such as Delta Lake, Spark, Kubernetes, Kafka, Click House, and/or Presto/Trino. Experience building large-scale batch and streaming pipelines with strict SLA and data quality requirements. Must possess excellent communication, analytical, and problem-solving skills. Demonstrated experience working with diverse data sets and frameworks across multiple domains-financial experience is not required, but a strong plus. Recent hands-on experience with AWS Cloud development, deployment, and monitoring necessary. Demonstrated experience working on an Agile team employing software engineering best practices, such as GitOps and CI/CD, to deliver complex software projects. The ability to react quickly and accurately to rapidly changing market conditions, including the ability to quickly and accurately respond and/or solve math and coding problems, are essential functions of the role.

Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, age (40 and over), disability, military status, genetic information or any other basis protected by applicable federal, state, or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories. It is Jobot’s policy to comply with all applicable federal, state and local laws respecting consideration of unemployment status in making hiring decisions.

Sometimes Jobot is required to perform background checks with your authorization. Jobot will consider qualified candidates with criminal histories in a manner consistent with any applicable federal, state, or local law regarding criminal backgrounds, including but not limited to the Los Angeles Fair Chance Initiative for Hiring and the San Francisco Fair Chance Ordinance.