Senior Data Platform Engineer
About this role
This role is crucial for establishing and maintaining the foundational data ecosystem that powers Later's AI-powered platform. The company leverages proprietary data, including billions of social interactions, to provide trusted insights for influencer marketing, aiming to remove guesswork for brands. The Senior Data Platform Engineer will be responsible for designing, building, and evolving the entire data infrastructure, treating the platform itself as a product for internal consumers. This position exists to ensure that the data foundation is robust, scalable, and ready to support the growing needs of AI applications, such as LLMs and AI agents. It is ideal for an engineer who prefers building core systems and architecture over focusing solely on individual reports or models.
The successful candidate will work across the entire data lifecycle, from data ingestion and orchestration to storage, transformation, and final consumption by analysts and data scientists. They will make key architectural decisions regarding the interaction between GCP and AWS environments and ensure data is prepared for advanced AI use cases. This role requires a strong platform mindset, focusing on creating reusable tooling and standards that improve the efficiency for dependent teams. It is suited for someone who enjoys tackling complex system design challenges and driving technical improvements across the organization.
Candidates who thrive in an environment where they build the core systems that enable data-driven decision-making and directly support AI product development will find this opportunity valuable. This is a chance to own a critical piece of the technology stack, directly impacting how Later delivers on its promise of bridging creativity and performance for brands.
What you will do
- Design, build, and evolve the core data platform infrastructure that moves data from its source to decision-making points.
- Own the scalable infrastructure encompassing data ingestion, orchestration, storage, transformation, and consumption across BigQuery and AWS.
- Make significant architectural decisions regarding data flow and modernization efforts for existing systems.
- Develop reliable batch and real-time data pipelines, including implementing dbt transformation layers.
- Shape the ingestion strategy by evaluating tools like Fivetran against custom connector solutions.
- Build and maintain the APIs and services necessary for secure, cost-aware data movement between GCP and AWS.
- Implement infrastructure as code practices and automate deployment using CI/CD pipelines.
- Establish observability, data quality checks, access controls, and performance optimization strategies.
What you need
- Possesses at least six years of experience in data engineering, backend engineering, or platform engineering.
- Demonstrated track record of owning production data systems at scale and successfully improving their reliability, performance, and cost.
- Strong proficiency in backend programming languages such as Python or similar, coupled with solid SQL skills.
- Hands-on cloud experience is required, ideally with GCP and BigQuery, and comfort working across multiple cloud environments.
- Experience with infrastructure as code, CI/CD practices, and workflow orchestration tools is necessary.
- Familiarity with batch and streaming architectures, along with a working understanding of security, access control, and data governance is essential.
- The ability to make sound architectural decisions and clearly articulate the tradeoffs to both technical and non-technical stakeholders is required.
Nice to have
- Kubernetes
- Experience migrating or redesigning orchestration systems
- Managed ingestion tools like Fivetran
- Experience building internal platforms or tooling that other engineers adopt
- Data foundations for AI, such as vector stores, feature pipelines, or governed LLM access
Benefits
- $125,000-205,000 USD salary range
Skills and tech stack
Questions candidates ask
What is the remote policy for this role?
The job is listed with locations in Boston, MA; San Francisco, California, United States; and Vancouver, British Columbia, Canada.
What is the expected compensation range?
The salary offered for this role is between $125,000 and $205,000 USD.
What is the primary technology stack used for the data platform?
The analytics platform runs on GCP and BigQuery, while operational databases reside in AWS.
What is the team structure like?
The role involves partnering with AI/ML, product, and engineering teams to understand their data needs.