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Описание вакансии
TL;DR
Middle Data Engineer (ClickHouse): Design, build, and optimize analytical data models and ETL/ELT pipelines in a ClickHouse-based warehouse with an accent on SQL, Python, dbt, Airflow, and CDC-based ingestion. Focus on improving pipeline performance and reliability, monitoring data quality, and developing reliable data models for Risk, Collections, Marketing, Finance, and Data Science teams.
Plazo Technologies is looking for Middle Data engineer in Poland
🔺What you'll do:
• Design, build and optimize data models and transformation pipelines in our ClickHouse-based warehouse.
• Develop and maintain ETL/ELT ingestion from operational databases, event streams and third-party APIs.
• Improve performance, stability, and cost of existing pipelines and queries as data volumes grow.
• Own data quality - automated tests, freshness and anomaly monitoring, and investigation when something looks wrong.
• Work directly with Risk, Collections, Marketing, Finance and Data Science teams to turn business questions into reliable data models.
• Support analysts and BI users, and reduce recurring manual requests by productising them.
🔺What we're looking for:
• 3+ years of hands-on experience as a Data Engineer, including work in a production analytical warehouse.
• ClickHouse - at least 1 year of practical experience. This is a must. Table engines, partitioning, materialized views, and the ability to diagnose slow or memory-heavy queries.
• Strong SQL, including window functions, array functions, complex joins and incremental logic on large tables.
• Confident Python for data processing, integration and automation.
• Practical experience with Apache Airflow - building and debugging DAGs, retries, backfills.
• Understanding of streaming and CDC-based replication (Kafka, Debezium or equivalent).
• Practical experience with dbt - incremental models, tests, project structure.
• English at intermediate level or above.
🔺Nice to have:
• Experience with BI tools such as Tableau or Apache Superset.
• Experience with data quality / observability frameworks.
• Fintech or lending background - credit lifecycle, delinquency, provisioning, cohort and LTV reporting.
• Understanding data modelling and DWH architecture in-column-oriented DB.
• Spanish.
🔺Our stack:
Languages: SQL, Python
Warehouse: ClickHouse
Transformation: dbt
Orchestration: Apache Airflow
Streaming & ingestion: Kafka, CDC
Visualization: Apache Superset, Tableau
Infrastructure: Prometheus, Grafana, Docker, Git
📩 Apply:
#dataengineer #clickhouse #sql #python #kafka #datajobs #itjobs #hiring
🔺What you'll do:
• Design, build and optimize data models and transformation pipelines in our ClickHouse-based warehouse.
• Develop and maintain ETL/ELT ingestion from operational databases, event streams and third-party APIs.
• Improve performance, stability, and cost of existing pipelines and queries as data volumes grow.
• Own data quality - automated tests, freshness and anomaly monitoring, and investigation when something looks wrong.
• Work directly with Risk, Collections, Marketing, Finance and Data Science teams to turn business questions into reliable data models.
• Support analysts and BI users, and reduce recurring manual requests by productising them.
🔺What we're looking for:
• 3+ years of hands-on experience as a Data Engineer, including work in a production analytical warehouse.
• ClickHouse - at least 1 year of practical experience. This is a must. Table engines, partitioning, materialized views, and the ability to diagnose slow or memory-heavy queries.
• Strong SQL, including window functions, array functions, complex joins and incremental logic on large tables.
• Confident Python for data processing, integration and automation.
• Practical experience with Apache Airflow - building and debugging DAGs, retries, backfills.
• Understanding of streaming and CDC-based replication (Kafka, Debezium or equivalent).
• Practical experience with dbt - incremental models, tests, project structure.
• English at intermediate level or above.
🔺Nice to have:
• Experience with BI tools such as Tableau or Apache Superset.
• Experience with data quality / observability frameworks.
• Fintech or lending background - credit lifecycle, delinquency, provisioning, cohort and LTV reporting.
• Understanding data modelling and DWH architecture in-column-oriented DB.
• Spanish.
🔺Our stack:
Languages: SQL, Python
Warehouse: ClickHouse
Transformation: dbt
Orchestration: Apache Airflow
Streaming & ingestion: Kafka, CDC
Visualization: Apache Superset, Tableau
Infrastructure: Prometheus, Grafana, Docker, Git
📩 Apply:
#dataengineer #clickhouse #sql #python #kafka #datajobs #itjobs #hiring
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