Data Engineer

Middle Data Engineer (BI / Analytics Enablement)

We are looking for a Data Engineer to own the end-to-end data flow: ingestion → processing → data marts → BI access → monitoring & support. This is a DE-first role focused on pipelines, data modeling, and data quality. You will also collaborate with analysts and stakeholders—building BI-ready marts, aligning metric definitions, supporting dashboards, and enabling monitoring for releases and experiments.

Responsibilities

Design and maintain data layers (staging, operational data layer, marts) and deliver analytics-ready data marts.

Develop and operate ETL/ELT pipelines (orchestration, retries, alerts, SLAs).

Build integrations with internal data sources and external partners.

Optimize pipeline performance and query efficiency (speed, stability, resource usage).

Implement data quality practices: validations, consistency checks, anomaly monitoring.

Make data BI-friendly: consistent semantics, shared metric definitions, “single source of truth.”

Translate business needs into metrics, tables, and dashboards, and clearly communicate metric changes.

Requirements

3+ years in Data Engineering / Analytics Engineering.

Strong SQL skills (window functions, complex aggregations, optimization, dimensional/metric modeling).

Proficient in Python for pipelines and tooling.

Hands-on experience with Apache Airflow and Apache Spark.

Understanding of data warehouse principles and operational ownership (quality, lineage, access).

Experience with Git and solid engineering practices.

English B2+ or higher.

Nice to Have

Experience with ClickHouse, S3-compatible storage, Docker/Kubernetes, Tableau/Metabase.

Experience in logistics, delivery, or ride-hailing domains.

Skills: mysql,kubernetes,sql,airflow,metabase,pyhton,clickhouse,tableau,spark