Data Engineer

Position: Staff Data Engineer
Job-:
Information Technology

Location:

Chicago, IL, United States;
New York, NY, United States

Schedule:

Full time Posted:
Qualifications Basic Qualifications Bachelor's degree in Computer Science, Engineering, MIS, or related field preferred.
12+ years of experience in data engineering or software engineering, with demonstrated experience architecting data platforms and pipelines ert-level SQL and strong proficiency in Python (Scala or Java a plus) for large-scale data processing and transformation.

Deep experience with cloud data platforms (e.g., Databricks, Snowflake, Synapse, Big Query, Redshift) and cloud-native architecture patterns.

Deep understanding of distributed systems, data modeling (dimensional, data vault, lakehouse), and ETL/ELT architecture.

Hands-on experience designing and implementing Master Data Management (MDM) solutions, including entity resolution, match/merge, golden records, and reference/hierarchy management (e.g., Informatica, Reltio, Profisee, or similar).Hands-on experience building or integrating agentic AI systems, LLM-powered applications, RAG pipelines, or AI agent orchestration frameworks (e.g., Lang Chain, Auto Gen, Semantic Kernel, MCP).Experience building backend data services and APIs (REST/GraphQL), with comfort working across the full stack.

Strong background with both relational (SQL) and No

SQL data stores, plus data lake/lakehouse formats (Delta, Iceberg, Parquet).Deep understanding of CI/CD pipelines, infrastructure as code, and Dev Ops/Data Ops practices.

Proven track record of leading large-scale technical initiatives across multiple teams.

Demonstrated ability to mentor engineers and influence technical direction without direct reporting authority.

Preferred Qualifications

Experience with data governance, lineage, and cataloging tools (e.g., Unity Catalog, Microsoft Purview, Collibra, Alation).Experience designing multi-agent systems, tool-calling architectures, or retrieval-augmented generation (RAG) pipelines.

Experience with event-driven architectures and streaming/real-time data processing (e.g., Kafka, Event Hubs, Kinesis, Flink, Spark Structured Streaming).Experience building the data layer for ML/AI, including feature stores, vector databases, embeddings, and ML/LLMOps.

Familiarity with containerization and orchestration (Docker, Kubernetes) and workflow orchestration (Airflow, Dagster, dbt).Prior experience in commercial real estate, fintech, or operations/transaction systems.

Track record of speaking, writing, or open-source contributions that demonstrate technical thought leadership, especially in applied AI or data.

Why Join Us?

Shape the technical direction of business-critical data platforms at enterprise scale, including master data management and next-generation agentic AI  part of a high-impact team where ownership, innovation, and technical excellence drive success.

Competitive compensation, growth opportunities, and access to world-class engineering, data, and AI resources.

Collaborative Culture:
Join a high-caliber team with deep expertise across data engineering, cloud, MDM, agentic AI, and distributed systems.

Growth & Learning:
Access world-class learning resources and mentorship to advance your career.

Work-Life Balance:
Flexible working hours and hybrid options.

Benefits:
Comprehensive health, dental and vision insurance.

If you're passionate about architecting scalable data platforms, building trusted master data and agentic AI-driven solutions, and shaping engineering culture, we'd love to hear from you!

Apply now and help redefine the future of data and AI at scale!

Salary Language:

The expected base salary for this position ranges from $190,000 to $225,000 annually. The actual base salary will be determined on an individualized…