We are redirecting you to the source. If you are not redirected in 3 seconds, please click here.

VP Data Engineering at Consumer Edge. . Location: New York (remote). This role is remote (US-based; east coast preferred). . Company Overview. . Join a dynamic team that's redefining consumer data analytics. We empower top investment firms and global consumer and corporate brands with cutting-edge insights into consumer spending, leveraging privacy-compliant data across geographies. Our real-time intelligence and merchant-level benchmarks give clients a competitive edge—and you'll be at the forefront of it all.. . Role Summary. . We're looking for a seasoned . VP of Data Engineering. to lead our data engineering team and take ownership of the infrastructure that powers everything we do. Because data . is. our business, this role carries significant weight: the reliability, scalability, and quality of our data pipelines directly impacts our customers and our revenue.. . You'll manage ~15 engineers across 3 data engineering teams, set technical direction across our GCP-based data platform, and work closely with data operations, product, and commercial teams to ensure we can continuously ingest, process, and deliver alternative datasets at scale — with the rigour that financial services clients demand.. . Your Main Responsibilities. . Team Leadership. . . Lead, mentor, and grow a team of data engineers, building a culture of ownership, craft, and continuous improvement. . Own hiring, onboarding, and performance management for the data engineering function. . Act as a technical role model — setting high standards while remaining approachable and supportive. . . Data Platform & Infrastructure. . . Own the architecture, reliability, and evolution of our GCP data platform — including BigQuery, Cloud Composer/Airflow, Dataflow, Pub/Sub, and GCS. . Design and maintain robust, scalable pipelines for ingesting, transforming, and serving diverse alternative datasets (web, CPG, transaction data, etc.). . Drive infrastructure best practices: cost optimisation, observability, incident response, and disaster recovery. . Ensure data security, access controls, and compliance standards appropriate for regulated financial services clients. . . Strategic & Cross-functional. . . Translate business priorities and client requirements into a clear, deliverable technical roadmap. . Partner with data operations, data science, and product teams to accelerate dataset onboarding and expand platform capabilities. . Represent data engineering at the leadership level — contributing to company strategy and advocating for data quality as a core business value. . . We’re looking for someone with. . Experience. . . 10+ years in data engineering, with at least 3 years in a leadership or management role (managing managers and teams). . Proven experience building and operating large-scale data pipelines on . Google Cloud Platform. . Experience in fintech, alternative data, financial data, or another data-as-a-product environment strongly preferred. . Track record of delivering high-quality data infrastructure in a fast-moving, commercially sensitive context. . . Technical Skills. . . Deep expertise across the GCP data stack: BigQuery, Dataflow, Pub/Sub, GCS, Cloud Composer, and related services. . Hands-on experience with dbt (Core or Cloud) for scalable transformation layer design, including modeling patterns, testing frameworks, and documentation standards. . Strong understanding of data pipeline design, ELT/ETL patterns, data modelling, and workflow orchestration. . Solid grasp of data governance, quality frameworks, and security best practices. . Familiarity with the unique challenges of alternative data — diverse formats, inconsistent schemas, high ingestion volumes, and strict data provenance requirements. . Practical experience with infrastructure-as-code tooling (Terraform and/or Pulumi) for provisioning and managing cloud resources; able to set IaC standards and review infrastructure changes with the same rigour applied to application code. . Strong proficiency in Python and SQL; comfortable reviewing code and setting engineering standards across the team.. . . Leadership & Soft Skills. . . Excellent communicator with the ability to engage engineers, data scientists, and commercial stakeholders alike. . Strong hiring instincts and a genuine passion for developing people. . Pragmatic and decisive — able to balance technical rigour with commercial urgency. . High ownership mindset; comfortable operating with autonomy in a high-stakes environment. . .  . Nice to Have. . . Experience supporting data science or ML teams with feature engineering infrastructure. . Familiarity with data licensing, provenance tracking, or data vendor management. . Experience with data mesh or data-as-a-product organisational models. . Open source contributions or published technical work. . . Why Join Consumer Edge. . At Consumer Edge, the data engineering team isn't a support function - it's a core part of how we deliver value to clients. You'll be joining at a critical stage of growth, with the opportunity to shape the platform, the team, and the standards that the entire business depends on.. . We offer a competitive salary, an extensive benefits package including 401(k) match, paid parental leave, flexible and generous time off, work-from-home flexibility, and a vibrant work environment conducive to professional growth and innovation. Join our team and play a significant role in driving data-driven decision-making, shaping the future of global consumer insights.. . Compensation and Benefits. . The annual base salary for this role is between $270,000– $300,000  based on experience, with the opportunity for a performance-based bonus, company equity, 401(k) matching, work-from-home flexibility, and subsidized health benefits.. .  . . Note Consumer Edge is currently hiring employees who reside in the following states or in Washington, DC:  CA, CO, CT, FL, ID, IL, LA, MA, MD, NC, NJ, NY, PA, RI, TN, TX, UT, VA, WA, WI . . . #LI-Remote. . #LI-DN.