Ruby Labs

consumer products, health, education, entertainment

DataEngineer

Ukraine FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Data Engineer at Ruby Labs. Skills: ClickHouse, event-driven pipelines, financial data modeling, Google Cloud. Design event pipelines. Build data pipelines”

What You'll Achieve.

Deliver reliable, low-latency data products; Ensure high-quality, well-typed billing and payments events; Ship analysts safely on top of the platform

Industry & Context.

consumer products, health, education, entertainment
Problems you'll solve

Investigate anomalies; Perform root-cause analysis; Drive fixes end-to-end

Eligibility Requirements

Located within approximately ± 4 hours of CET

What They're Looking For.

Must Have

Production experience with ClickHouse, data modeling (MergeTree family, projections, materialized views), query tuning, partitioning/sharding, operational awareness, experience designing event-driven, real-time analytics pipelines (Kafka / Pub/Sub / Kinesis or equivalent), schema design, backfills, replay, Hands-on with Google Cloud data stack (Pub/Sub, GCS, BigQuery, Cloud Run / GKE, IAM), Production experience with Apache Airflow (DAG design, sensors, retries, SLAs, idempotent tasks, incremental loads), Advanced SQL (complex joins, window functions, incremental logic, performance-aware query writing), Python for data engineering (pipelines, transformations, tests, tooling), Git workflow (PRs, code review, CI for SQL/pipelines, versioning of data logic), Experience working with financial / payments / subscription data, Ability to communicate trade-offs and findings clearly to both technical and non-technical stakeholders

Nice to Have

Tinybird experience (pipes, endpoints, materializations, performance tuning), dbt, Dataflow / Beam, Spark, or other large-scale processing frameworks, Experience with risk/fraud or billing & payments analytics (auth rate, dispute rate, dunning recovery, BIN/issuer analysis), Experience with experimentation/A test data infrastructure, Terraform / IaC, Docker, Kubernetes for data infra

What You'll Do.

Design event pipelines

Deliver low-latency data products

real-time data pipelines

Optimize ClickHouse schemas

Model core financial datasets

Own data observability

Investigate anomalies

Perform root-cause analysis

Drive fixes end-to-end

Partner on event schemas

Build internal tooling

How You'll Work.

Team & Collaboration

Partner with Backend/Platform on event schemas and instrumentation; Communicate trade-offs and findings clearly to technical and non-technical stakeholders

Communication Scope

Ability to communicate trade-offs and findings clearly

Full Job Description

ABOUT US Ruby Labs is a leading tech company that creates and operates innovative consumer products. We offer a diverse range of opportunities across the health, education, and entertainment industries. Our innovative teams are driving the future of consumer-led products, and we're always looking for passionate individuals to join us. Learn more about our story at: https://rubylabs.com/about-us/ ABOUT THE ROLE We're looking for a Data Engineer with deep experience in event-driven, real-time financial analytics and strong technical skills in ClickHouse. You will own the data platform that powers Paynext payments and billing analytics: design event pipelines, build and optimize datasets, and deliver reliable, low-latency data products that product, finance, risk, and operations teams rely on daily. KEY RESPONSIBILITIES - Design and build event-driven, real-time data pipelines on ClickHouse, Google Cloud, and Airflow to power dashboards and self-serve analytics. - Optimize ClickHouse schemas, materialized views, and queries for performance, correctness, and cost. - Model core financial datasets for payments and subscriptions: authorizations, declines, refunds, chargebacks, disputes, dunning, MRR/ARR, LTV, churn, cohort retention. - Own data quality and observability: tests, monitoring, alerting, lineage, and SLAs for freshness and correctness on Tier-1 datasets. - Investigate anomalies and data-quality issues in financial data, perform root-cause analysis, and drive fixes end-to-end (instrumentation → pipeline → metric). - Partner with Backend/Platform on event schemas and instrumentation to ensure high-quality, well-typed billing and payments events. - Document logic (metric definitions, tables, pipeline behavior) and build internal tooling/templates that let analysts ship safely on top of the platform. QUALIFICATIONS - Production experience with ClickHouse is mandatory: data modeling (MergeTree family, projections, materialized views), query tuning, partitioning/shar

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