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Senior Data Engineer

11 hours, 11 minutes ago
United Kingdom
Full-time
Senior
Data Engineer
Software Development
Apache Airflow Apache Spark Argo CD AWS ClickHouse Databricks Docker GCP GitOps Go Grafana gRPC Helm Kafka Kubernetes OpenTelemetry Prometheus Python SQL Terraform
Apply Now
Merkle Science

Merkle Science

Merkle Science provides a predictive crypto risk and intelligence platform that specializes in next-generation threat detection, risk management, and compliance solutions for businesses, banks, and government agencies, enabling them to identify suspici...

Capital Markets
11-50
Founded 2018
$26M raised
View All Jobs 11

Description

  • Design, build and operate scalable, high-throughput data pipelines and platform systems for blockchain data across 30+ chains.
  • Build backend data services and loaders using Go and Python.
  • Design and evolve ClickHouse data models and analytical workloads for sub-second query performance.
  • Build incremental, idempotent Databricks pipelines processing billions of rows and tens of terabytes.
  • Improve platform scale, reliability, data freshness, performance and cost efficiency.
  • Investigate and resolve complex performance and reliability issues.
  • Partner with product, analytics and investigations teams to translate data needs into platform designs.
  • Set technical direction through architecture discussions, design reviews and code reviews.
  • Mentor engineers and strengthen engineering and operational practices.

Requirements

  • 5+ years of experience building and operating production data systems, including ETL and ELT pipelines.
  • At least 2 years owning systems relied on by other engineers.
  • Expert Python and strong SQL, including typed, tested code, asyncio and concurrency.
  • Production experience building incremental data models over billions of rows.
  • Production experience building and operating high-throughput Go services or data loaders.
  • Production ClickHouse experience, including MergeTree schema and sort-key design, materialized views, bulk loading and query tuning.
  • Production Databricks experience with PySpark, Delta Lake, Unity Catalog, incremental and idempotent tables, and compute-cost management.
  • Experience with large-scale pipelines spanning billions of rows and tens of terabytes, including partitioning, clustering and file-sizing trade-offs.
  • Production experience with Kafka, Airflow and Kubernetes, including delivery semantics, idempotent writes, backfills, failures, Docker and Helm; Google Cloud preferred, AWS acceptable.
  • Experience with blockchain data, graph or distributed key-value stores, Terraform, GitOps, observability tools, multi-source data platforms, AI-assisted development, or fintech, compliance or AML is preferred.

Benefits

  • Excellent health insurance.
  • Flexible time off and work/life-balanced hours.
  • Learning and development initiatives.
  • Mental health discussions and regular team-building sessions.
  • Industry-leading compensation.
  • Generous equity.
  • Career growth opportunities in a rapidly growing company.

Interested in this position?

Apply directly on the company website

Apply Now

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