Senior Data Engineer — Hybrid Data Platform Architect

Objective Partners

Chicago (IL)

Hybrid

USD 200,000 - 250,000

Full time

14 days+

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Benefits offered by this job

Base salary 200k–250k USD
Annual discretionary bonus
Comprehensive benefits

Job summary

Objective Partners is seeking a Senior Data Engineer to lead a core data platform in a hybrid setup in Chicago or New York. You will architect high-throughput data pipelines, ingest external feeds, and implement governance with strong collaboration across researchers and trading teams.

You will optimize storage formats and modern architectures while driving operational reliability, monitoring, and scalable tooling for end-user data discovery in a fast-paced financial environment.

Qualifications

  • 7+ years building enterprise-grade data platforms and pipelines.
  • Expert SQL with production-grade Python or Java.
  • Experience with modern data modeling and architecture choices.
  • Hands-on with Airflow, Dagster, Prefect, Kubernetes or Argo Workflows.
  • Experience with Delta Lake, Iceberg, Parquet, S3, ClickHouse, Cassandra or relational DBs.
  • Track record of data platform migrations and operational recovery.

Responsibilities

  • Architect and maintain scalable data pipelines and centralized platform.
  • Ingest and operationalize external data feeds with domain experts.
  • Implement governance: access control, lineage, schema, quality metrics.
  • Ensure ingestion pipelines reliability, schema updates, backfills, on-call support.
  • Build monitoring and validation tools for data quality across batches and streams.
  • Improve internal tooling to accelerate data discovery and integration.

Skills

SQL mastery
Python/Java
Data modeling
Workflow orchestration
Storage systems
Data platform migrations
Communication

Tools

Airflow
Dagster
Prefect
Kubernetes/Argo

Job description

Objective Partners is seeking a Senior Data Engineer to lead a core data platform in a hybrid setup in Chicago or New York. You will architect high-throughput data pipelines, ingest external feeds, and implement governance with strong collaboration across researchers and trading teams.

You will optimize storage formats and modern architectures while driving operational reliability, monitoring, and scalable tooling for end-user data discovery in a fast-paced financial environment.

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