2 months ago
Base Salary
$113k - $175k/yr
Responsibilities
- Lead pre-sales technical engagements, discovery workshops, architecture reviews, assessments, proofs of concept, RFP responses, and proposal content.
- Own the technical relationship with client data leaders and engineering teams, advising on architecture, feasibility, risk, and business outcomes.
- Deliver or lead complex Databricks-based data transformation programs through architecture, development, testing, deployment, and governance.
- Design and build reusable Databricks implementations, reference architectures, data models, production pipelines, and accelerators.
- Make day-to-day decisions on platform configuration, data modeling, tooling, integration risks, data quality, scope, and schedule.
- Conduct architecture reviews, code reviews, technical assessments, and contribute to technical standards and best practices.
- Explain Databricks architecture and data engineering decisions to C-suite, board, business, and technical audiences.
- Mentor engineers, contribute to internal knowledge management, and develop technical and client-facing capability.
- Represent Merkle's Databricks expertise in client forums, advisory boards, steering committees, vendor conversations, and thought leadership activities.
Requirements
- 8+ years building data platform implementations on cloud data warehouses, including at least 3 years of hands-on Databricks experience.
- Advanced SQL and Python skills with the ability to build production-quality data pipelines independently.
- Deep experience with relational and lakehouse data modeling, including Customer 360 and conformed data models.
- Demonstrated success participating in and leading complex, multi-phase delivery programs.
- Exceptional client-facing communication skills across C-suite, business, and technical audiences.
- Experience with data observability, pipeline automation, formal production change control, and cloud data architecture.
- Active use of AWS, GCP, or Azure cloud platforms.
- Regular use of AI coding assistants such as GitHub Copilot, Cursor, or Claude Code.
- Preferred: Databricks Certified Data Engineer Professional or Databricks Solutions Architect certification.
- Preferred: Databricks community participation, conference speaking, knowledge-sharing, governance and Unity Catalog implementation at enterprise scale.
- Preferred: Experience with Databricks AI capabilities, modern orchestration, adjacent customer data platforms, pre-sales discovery, and mentoring junior engineers.
Benefits
- Medical, vision, and dental insurance; life insurance; and short- and long-term disability insurance.
- 401k, flexible paid time off, at least 15 paid holidays annually, paid sick and safe leave, and paid parental leave.
- Full-time permanent position with a remote/hybrid arrangement in New York.
Tech Stack
Categories
Data EngineeringSolutions Engineering
About Dentsu
Dentsu is a global advertising and marketing services group that plans and buys media, develops creative campaigns, and builds data- and technology-led customer experiences for brands. It earns revenue from agency fees and media services across a network that includes Carat, iProspect, and Merkle. Founded in 1901 and headquartered in Tokyo, Dentsu is publicly traded in Japan and serves clients across many sectors worldwide.