Job Type: Contract
Contract Length: Long-term consulting opportunity
Pay Range: $60-$70/hr
Start Date: ASAP
Location: Hybrid (Boston or Needham, MA – 4 days onsite required)
About the Opportunity:
Our client, a leader in Financial Services, is looking for a skilled Enterprise Data Platform Engineer to join their team for a long-term consulting opportunity. This project involves building a brand-new Enterprise Data Platform in a true greenfield environment, focusing on establishing a scalable, enterprise-ready modern data platform architecture. This is an excellent opportunity for a hands-on engineer who enjoys building foundational platforms from the ground up and working closely with architecture and infrastructure teams.
Key Responsibilities & Deliverables:
This role is focused on the successful completion of specific tasks and deliverables. Your responsibilities will include:
- Designing and implementing end-to-end data ingestion pipelines using Azure services, including API-based ingestion and Azure Data Factory (ADF).
- Helping design and build a new enterprise data platform from inception and supporting platform provisioning and enterprise readiness initiatives.
- Building and managing lakehouse and data warehouse solutions, applying the medallion architecture (bronze, silver, gold layers).
- Developing and optimizing data transformations using PySpark, ensuring scalability, performance, and cost efficiency.
- Collaborating with engineering, architecture, and platform teams to contribute to best practices around governance, scalability, security, and operational excellence.
We are looking for someone with a proven track record of successful contract engagements. The ideal candidate will have:
- Strong Data Engineering experience in modern cloud data environments.
- Hands-on experience or strong working knowledge of Microsoft Fabric is highly preferred. Candidates with strong Databricks or Snowflake backgrounds will also be considered.
- Proven experience working in Azure for data ingestion and orchestration, with strong experience in Azure Data Factory (ADF).
- Proficiency in PySpark for large-scale data transformations and optimization.
- Solid understanding of data storage formats (CSV, JSON, and Parquet) and experience with data warehouse and lakehouse architectures.
- Practical experience implementing medallion architecture patterns and a strong foundation in data modeling concepts.
- Experience working in greenfield or platform build-out environments is highly desirable.
- Strong cloud and enterprise architecture mindset.
- Strong communication skills to operate effectively in an evolving, cross-functional, and client-facing environment.
