Senior Data Platform Engineer

About the role

The role centers on scalable data infrastructure for blockchain applications on GCP, with Aleo L1 indexers and privacy-focused architectures. It blends data engineering and backend development to power explorers, wallets, and analytics.

Software engineers turn product ideas into working code. Engineers work in small teams, review each other's work, and ship in small batches. Most teams follow agile practices such as sprints and daily standups. Engineers also write tests, fix bugs, and improve performance. The field values clear communication as much as technical skill. Engineers spend part of every week on planning, code review, and debugging, not just writing new code. The ability to explain a technical decision in plain words separates strong engineers from the rest.

Key facts

What you'll do

Scalable data infrastructure on GCP is built, scaled, and maintained to support high-throughput blockchain workloads.

Data pipelines ingest and process streams from Aleo L1 blockchain indexers to power explorers, APIs, and analytics.

Aleo's zero-knowledge privacy and cryptographic constraints are handled by data models that store and query proofs and state efficiently.

APIs serving mobile privacy wallets and external products are developed, optimized, and operated for reliable data delivery.

Postgres and BigQuery databases are managed and tuned to meet performance, cost, and reliability targets.

Requirements from product and engineering are analyzed to deliver high-performance data APIs and platform features.

Data platform performance and cost are profiled, tested, and iteratively improved for optimization.

Deployment and operations of data environments on GCP are automated with infrastructure-as-code using Terraform and Helm.

Requirements

6+ years of experience managing production data systems as a Data Platform, Data Engineering, or Core Backend engineer.

Node.js and TypeScript proficiency enables efficient API development for data services.

SQL skills optimize relational databases like Postgres and cloud warehouses such as BigQuery.

Infrastructure automation with Terraform and Kubernetes on GKE manages cloud resources reliably.

Clear communication and end-to-end ownership drive critical technical initiatives to successful completion.

Nice to have

Real-time streaming with Kafka, Debezium, Flink, Airflow, or dbt improves freshness and reliability of privacy-aware pipelines.

Web3 infrastructure knowledge supports indexing zero-knowledge and privacy-focused networks like Aleo.

Observability solutions built with Prometheus, Grafana, or GCP native tools strengthen monitoring and alerting.

Practical notes

Typical interview steps

Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds. Candidates often solve a coding problem, discuss past projects, and answer system design questions. Some loops include a take-home task. Final rounds typically cover team fit and give candidates a chance to ask questions. Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer. Practicing a few problems aloud and reviewing your own past projects are the best preparation.

Career growth

Engineering careers usually progress from individual contributor to senior, staff, and principal levels. Some engineers move into management and lead teams of five to twenty people. Others stay on the technical track. Growth follows demonstrated impact, not tenure alone. A typical engineering ladder has clear levels with defined expectations for scope, quality, and mentorship. Moving up usually requires owning outcomes end to end rather than completing assigned tickets.

Questions to ask

Good questions to ask the employer in the interview: what does success look like in the first six months, how is the team structured, what is the current biggest challenge, and how are decisions made. Asking about growth paths and the review process is also well received. Employers expect questions, and good ones show preparation.

About the company

At Provable, our mission is to redefine trust and privacy in the digital world. By creating tools that simplify the complexities of zero-knowledge technology, we empower developers to build applications that prioritize security, user control and scalability.