Data Engineer (Mid) — ClickHouse / Analytics / BI

About the role

We’re hiring our first Data Engineer to build and own the analytics/data foundation. You’ll work across product, engineering, and business stakeholders to turn raw operational data into trusted datasets, dashboards, and metrics. This is a hands-on role with real ownership: you’ll design pipelines, shape our data model, and help establish the practices that will scale with the company.

What you’ll do

• Build and maintain data pipelines from product and operational systems into our analytics stack.

• Design and operate a ClickHouse-based analytics warehouse (schemas, partitioning, performance tuning, retention).

• Define and maintain core business metrics (single source of truth), dimensional models, and curated datasets.

• Deliver BI reporting: dashboards, self-serve datasets, and recurring management reports.

• Improve data quality: validation checks, anomaly detection, SLAs, lineage documentation.

• Partner with engineers to instrument products/events and ensure data is captured correctly (events, logs, audits).

• Support ad-hoc analysis requests and help stakeholders interpret data correctly.

• Establish “first hire” foundations: conventions, documentation, runbooks, and lightweight governance.

Requirements (must-have)

• 3+ years (or equivalent) in Data Engineering / Analytics Engineering.

• Strong SQL, experience modeling analytics datasets (star schema / dimensional modeling).

• Hands-on experience with ClickHouse (or another columnar OLAP DB) and performance optimization.

• Practical experience building ETL/ELT pipelines (batch and/or near-real-time).

• Familiarity with a BI tool (e.g., Metabase, Superset, Power BI, Looker, Tableau) and working with stakeholders.

• Comfortable operating production data workflows: monitoring, retries, backfills, incident fixes.

Nice to have

• Experience with tools like Airflow / Dagster / Prefect, dbt, Kafka, Spark/Flink (any subset).

• Experience with event analytics (product events), log analytics, or audit trails.

• Python (or another scripting language) for pipeline logic and automation.

• Understanding of security/compliance needs (access control, retention, auditability), especially in regulated environments.

What we offer

• First data hire: real ownership, influence on architecture and standards.

• Close collaboration with engineering/product leadership; your work will directly impact decisions.

• Competitive compensation and flexible work setup (details based on location).