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Sr. Data Engineer
- Chicago, Illinois, United States
- Chicago, Illinois, United States
À propos
Design, build, and maintain robust data pipelines and data lake architecture for both batch and real-time streaming use cases, including high-volume, low-latency data processing.
Improve observability, alerting, and SLOs across data systems so pipelines are easier to monitor and issues are caught early.
Optimize ETL/ELT workflows for performance, scalability, and fault tolerance.
Develop dbt workflows to onboard Evaluation Partners and create end-of-day reporting for partner analysis.
Build and support event‑driven architectures and scalable platform components.
Contribute to the orchestration and automation of workflows.
Integrate complex financial APIs and third‑party data sources into internal systems.
Collaborate with analytics, product, and ML engineers to develop and deploy reliable data products.
Work on feature pipelines and model‑ready data to support ML engineers.
Promote high standards in code quality, testing, and platform reliability.
Participate in Agile ceremonies and foster a collaborative, growth‑oriented team culture.
Qualifications
Bachelor’s degree in Computer Science, Engineering, or a related field.
5+ years of experience in data engineering, platform engineering, or backend development.
Strong skills in SQL and Python for building and testing data solutions.
Hands‑on experience with GCP and GCP data products (BigQuery, Cloud SQL, Cloud Storage, etc.).
Experience with AWS cloud services (S3, Glue, Athena, Kinesis) in addition to GCP; bonus for EMR.
Experience with CI/CD pipelines, infrastructure‑as‑code, and version‑controlled deployment workflows (e.g., Terraform, GitOps).
Hands‑on dbt experience building and maintaining dbt projects (models, tests, macros, documentation, CI).
Proficiency with workflow orchestration tools (e.g., Airflow, Prefect).
Knowledge of data lake architecture, including file formats (Parquet, Avro) and open table formats (Apache Iceberg).
Familiarity with event‑driven and service‑oriented architecture.
A track record of building automated, well‑tested, and observable data systems.
Comfortable working both independently and collaboratively in a fast‑paced Agile environment.
Hands‑on Kubernetes experience, especially around data workloads and containerised pipelines.
Experience with streaming technologies (e.g., Kafka, Spark Streaming, Flink) and comfort working with high‑volume, low‑latency data flows.
Experience with change data capture tools (e.g., Debezium, Kafka Connect) and real‑time data integration patterns.
Experience with BI tools like Looker Studio or QuickSight.
Experience with observability and monitoring tooling (e.g., Datadog, Grafana, Prometheus).
Background in fintech, trading, or derivatives.
Compensation The salary range for this role is $100,000.00 - $150,000.00 USD. In addition, this position will receive an annual target bonus of 10%, split 50% based on individual performance and 50% based on company/team performance.
Benefits
Generous PTO (18 days per year plus additional days for certain positions).
7 paid holidays annually and 5 conditional holidays.
1 service day annually.
401(k) with up to 3.5% company match.
Life and disability insurance fully covered by NinjaTrader.
We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal‑opportunity workplace.
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Compétences linguistiques
- English
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