Senior Data Engineer

About the role

Beacon is seeking a talented Senior Data Engineer to join our data team and help solve complex and interesting data-centric problems for our diverse clients. As a Senior Data Engineer, you will develop modern data architecture approaches to meet key business objectives and provide end-to-end data solutions. No two days will be the same, and you should anticipate supporting multiple clients and projects concurrently in a fast-paced and highly collaborative environment.

Responsibilities

• Develop large-scale batch and/or streaming data pipelines and data-centric applications in production.
• Architect and oversee delivery of large-scale ELT pipelines, cloud data warehouses, and containerized services across client environments, guiding engineers through implementation.
• Establish infrastructure-as-code standards and oversee their implementation.
• Set and enforce security standards for client data — access controls, role-based permissions, and data isolation across environments.
• Maintain strong expertise and knowledge of current and emerging technologies and products.
• Provide architectural recommendations, solutions, approaches, inherent tradeoffs, and communicate these concepts clearly to the client.
• Formulate technical roadmaps and technology solutions that address client needs and challenges and support their business strategies and goals.
• Engage with business partners as a technology consultant and provide technical leadership in an enterprise environment to ensure delivery of exceptional technical solutions.
• Become a trusted and valued partner of the client C-suite executives and team.
• Understand business context and transfer that knowledge to solution design, recommended next steps, and approaches around data to support business needs.
• Provide technical guidance and mentorship as a technical data lead.

Qualifications

• Experience building large-scale batch and/or streaming data pipelines and data-centric applications in production.
• Fluency in SQL and Python for building production-grade data systems.
• Hands-on experience architecting cloud infrastructure — compute, networking, storage, security, and cost considerations.
• Meaningful experience across multiple database technologies — relational, cloud MPP warehouses, and NoSQL — including migrating workloads from legacy or on-prem systems to cloud platforms.
• Experience building data extraction and integration workflows across diverse sources — REST and GraphQL APIs, webhooks, flat files, and vendor systems.
• Experience delivering machine learning solutions — data pipelines for model training, model deployment, and production operations (MLOps).
• Ability to advise clients on AI strategy — identifying high-value AI/ML use cases and translating them into data architecture and delivery plans.
• Experience shaping enterprise data strategy — data governance, data quality, and stewardship across the data lifecycle.
• Deep working knowledge of data security and privacy practices — RBAC, row/column-level security, data masking, PII handling, and encryption, with familiarity with regulations such as GDPR, HIPAA, and CCPA.
• Comfortable leading technical delivery teams, with the ability to dive into code when needed — and a track record of delivering data engineering solutions across multiple industries and organizations.