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# Sr. Data Engineer (UP)

- **Company:** OBJECTIVE PARTNERS LLC
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Salary:** $200,000 - $250,000
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Airflow, Amazon S3, Data Discovery, Data Governance, Serialization, Relational Databases, Protocol Buffers, Python (Programming Language), Simple Data Format, SQL Databases, Data Streaming, Parquet, Data Ingestion, Apache Spark, Usage Tracking, Data Lakes, Kubernetes, Apache Flink, Cassandra, Avro, Dask, Apache Kafka, Data Management, Vertica, Data Pipelines
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25197_9182ec63896fa0fa27499648938321a8

## About the Role

* 7+ years of dedicated experience building enterprise-grade data platforms and pipeline infrastructure.
 * Expert-level mastery of SQL along with production-grade proficiency in either Python or Java.
 * Demonstrated expertise in modern data modeling paradigms and architecture trade-offs.
 * Hands-on experience orchestrating complex workflows using systems such as Airflow, Dagster, Prefect, or Kubernetes/Argo Workflows.
 * Proven experience with modern storage systems and file formats (e.g., Delta Lake, Iceberg, Parquet, S3, ClickHouse, Cassandra, or relational databases).
 * Track record of executing non-trivial data platform migrations and managing operational recovery processes (batch reprocessing, backfills, queue monitoring).
 * Strong communication skills and the ability to thrive in a collaborative, fast-paced trading/financial environment., * Familiarity with distributed compute and streaming frameworks (e.g., Flink, Spark, Polars, Dask, Kafka).
 * Experience handling binary serialization standards such as Avro, Arrow, Protobuf/gRPC, or Thrift.
 * Background in financial markets, market data ingestion, or high-throughput analytics platforms.

## Description

* Architect, construct, and maintain scalable data pipelines and centralized platform architecture supporting enterprise-wide analytics and quantitative trading workflows.
 * Evaluate, ingest, and operationalize external vendor data feeds in close collaboration with domain experts and quantitative analysts.
 * Implement robust data governance frameworks, including access control, lineage, schema management, usage tracking, and automated quality metrics.
 * Oversee operational stability of ingestion pipelines, managing schema updates, data backfills, dead-letter queue resolution, and rotating on-call support.
 * Build automated monitoring and validation tools to preemptively detect and resolve data anomalies across batch and streaming pipelines.
 * Drive continuous improvement of internal tooling and self-service capabilities to accelerate data discovery and integration for end users.