Job Type: Contract to Hire (CTH)
Contract Length: End of Year (EOY)
Pay Range: $60 - 80/hour
Start Date: 6/15/26
Location: Hybrid—3 days a week in the NYC office, conveniently located next to MSG and Penn Station.
About the Opportunity:
Our client, a leader in FinTech (transforming the syndicated loan market), is looking for a skilled Senior Data Platform Engineer to join their team for an End of Year engagement. This high-impact role is primarily focused on data engineering, with a secondary responsibility in reporting and dashboard delivery. The core mission is to transform operational (OLTP) data from multiple source systems into clean, analysis-ready (OLAP) datasets using a lakehouse medallion architecture. The role will work closely with the Data Architect and his team to evolve reporting offerings. The team is well-funded, having recently raised $40M, and is rapidly expanding.
Key Responsibilities & Deliverables:
This role is focused on the successful completion of specific tasks and deliverables. Your responsibilities will include:
- Designing and Implementing ELT Pipelines: Designing, implementing, and operating ELT pipelines to ingest data into the lakehouse.
- Data Modeling and Architecture: Applying Medallion architecture and semantic layering to deliver curated datasets for analysis.
- Data Quality & Observability: Establishing and enforcing standards for data quality, observability/alerting, and lineage; upholding daily/hourly SLAs for critical reports and datasets.
- Driving DataOps: Leading CI/CD practices for data code reviews, documentation, and environment promotion.
- Mentorship: Mentoring and unblocking teammates through code reviews, pairing, and knowledge-sharing practices.
- Reporting & Analytics: Partnering with Product to translate requirements into robust models, metrics, and dashboards, and supporting timely, trusted reporting for leadership and clients.
We are looking for someone with a proven track record of successful contract engagements. The ideal candidate will have:
- 5–7 years in data engineering or analytics engineering.
- Deep expertise in Strong SQL and practical experience with dbt for transformations and testing.
- Professional coding experience with both Java and Python.
- Hands-on experience with dimensional data modeling (e.g., star/snowflake schemas) and performance optimization.
- Experience operating data ware/lake-houses (including semantic layers, storage formats, and partitioning).
- Familiarity with CI/CD (DataOps), version control, and environment promotion.
- Experience with external client reporting, embedded analytics, and multi-tenant considerations (modeling, partitioning, access controls).
- Demonstrated ability to mentor or coach in software engineering practices.
