Note: The job is a remote job and is open to candidates in USA. Beacon Data is a full-stack data and growth consulting firm that helps clients optimize data environments and operationalize AI and machine learning use cases. The Senior Data Engineer will develop modern data architecture approaches, provide end-to-end data solutions, lead technical delivery across multiple clients and projects, and mentor data engineering teams.
Responsibilities
- 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 architectural recommendations, solutions, approaches, inherent tradeoffs, and communicate these concepts clearly to the client
- 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
- Improve Beacon teams through code review, documentation, technical guidance, and mentoring as a technical data lead
Skills
- • 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
- • Need to be eligible to work in the USA
- • Willing to commute periodically to client work sites
Company Overview