Senior Data Platform Engineer

Title: Senior Data Platform Engineer

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.

Our client, a leader in Fin Tech (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.

• 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 Data Ops:
  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.

• 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 (Data Ops), 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.