Lead Data Engineer

Job Title: Lead Data Engineer Job Title: Lead Data Engineer Location: Hybrid to NYC preferred but will consider fully remote candidates Contract Type: Contract to Hire About The Role This is a mostly remote position with a preference for candidates in the NYC metro area, though fully remote candidates will also be considered. The role requires travel to the New York City office approximately once per month. This is a contract-to-hire opportunity with the expectation of conversion to a permanent full-time role for the right candidate. Job Summary We are seeking a hands-on Lead Data Engineer to join a growing data team and play a foundational role in building out enterprise data engineering capabilities from the ground up. This individual will be a key contributor in critical near-term initiatives, such as a Master Data Management (MDM) record implementation using Reltio and a Google BigQuery implementation, while also contributing to the organization’s broader data modernization roadmap. Operating within a Microsoft-centric environment with Azure infrastructure and Oracle systems, the ideal candidate brings deep technical expertise, strong leadership instincts, and a builder mentality. This is a high-impact, ground-level opportunity to shape the data engineering function and influence the long-term platform strategy. Key Responsibilities Lead the design, implementation, and delivery of the Reltio MDM platform, including data modeling, record matching, survivorship rules, and integration with source systems. Architect and implement Google BigQuery as a core data platform, establishing pipelines, schemas, and best practices for scalable analytics workloads. Design, build, and maintain scalable data pipelines and ETL/ELT processes across Oracle, Azure, and Google Cloud platforms. Serve as a technical lead and hands-on contributor, setting engineering standards, conducting code reviews, and mentoring junior engineers. Collaborate with business stakeholders, data analysts, and technology teams to translate requirements into scalable data solutions. Contribute to the evaluation and adoption of emerging platforms including Databricks and Google Cloud 360. Establish data engineering best practices, documentation standards, and reusable frameworks to support a growing data organization. Ensure data quality, reliability, and security across all data assets and pipelines. Requirements 6+ years of hands-on data engineering experience with a track record of leading complex, enterprise-scale implementations. Hands-on experience implementing or operating a Master Data Management platform; Reltio experience strongly preferred. Proven experience designing and building data pipelines and analytics solutions on Google BigQuery. Strong experience with Oracle databases and Microsoft Azure cloud services. Proficiency in SQL and at least one scripting or programming language (Python preferred). Demonstrated ability to operate as both a technical lead and hands-on engineer simultaneously. Comfort working in a greenfield environment and building data capabilities from the ground up. Strong communication and collaboration skills with the ability to engage both technical and business stakeholders. Preferred Qualifications Experience with Databricks or familiarity with the Databricks Lakehouse platform. Familiarity with Google Cloud 360 or broader Google Cloud Platform services. Experience in a build-out or startup phase of a data organization. Background in legal, dispute resolution, or professional services industries. #J-18808-Ljbffr