2 Π΄Π½Ρ Π½Π°Π·Π°Π΄
BI / Analytics Engineer (AI / Data Platform)
4Β 000 - 6Β 000β¬
ΠΠ°ΠΊΠ°Π½ΡΠΈΡ ΠΈΠ· Telegram ΠΊΠ°Π½Π°Π»Π° - ΠΡΡΡ & Π‘ΠΎΠΏΡΠΎΠ²ΠΎΠ΄
ΠΠΎΠΊΠ°ΠΆΠ΅Ρ Π²Π°ΡΡ ΡΠΎΠ²ΠΌΠ΅ΡΡΠΈΠΌΠΎΡΡΡ ΠΈ Π½Π°ΠΏΠΈΡΠ΅Ρ ΠΏΠΈΡΡΠΌΠΎ
ΠΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ
#vacancy BI / Analytics Engineer (AI / Data Platform)
Location: Remote (Worldwide β EU & Global candidates welcome)
Salary: β¬4,000 β β¬6,000 gross/month (Market rate based on experience)
Employment: Full-time | Start: ASAP
Language: English B1+ (Confident conversational level required)
About the Project:
We are building a next-generation AI & Data Platform that combines modern analytics with Generative AI. You will work on integrating LLMs, RAG architectures, and agent-based solutions into robust data pipelines, enabling real-time insights and intelligent automation.
Tech Stack & Requirements:
Must Have:
β’ Role: Proven experience as BI Engineer, Analytics Engineer, or Senior Data Analyst.
β’ SQL: Advanced proficiency (complex queries, optimization, window functions).
β’ Databases: Hands-on experience with PostgreSQL, ClickHouse, and/or TimescaleDB.
β’ BI Tools: Experience building dashboards and reports (Apache Superset is a priority).
β’ Data Integration: Strong understanding of ETL/ELT processes; experience with Apache NiFi (or similar tools like Airflow/dbt).
β’ Communication: Confident English for daily collaboration with international teams.
Nice to Have:
β’ Python: Scripting for data analysis (pandas, polars, pyarrow).
β’ ML/AI Context: Understanding of ML pipelines and how to serve models.
β’ Cloud Storage: Experience with AWS S3 or equivalent object storage.
β’ Real-Time: Knowledge of streaming analytics and event-driven architectures.
β’ AI Stack Familiarity: Basic understanding of LLMs, RAG patterns, LangChain/LangGraph, and Vector DBs (e.g., Qdrant).
What You'll Do:
- Design and maintain scalable data models in PostgreSQL/ClickHouse/TimescaleDB.
- Build interactive dashboards and self-service analytics using Apache Superset.
- Develop and optimize ETL/ELT pipelines (using Apache NiFi) to ingest data from various sources.
- Collaborate with Data Scientists and AI Engineers to integrate LLM/RAG outputs into analytical workflows.
- Ensure data quality, consistency, and performance across the platform.
How to Apply:
To apply, please fill out the candidate form:
#BIEngineer #AnalyticsEngineer #DataPlatform #SQL #ClickHouse #Superset #NiFi #AI #LLM #RemoteJobs #Hiring #DataEngineering
Location: Remote (Worldwide β EU & Global candidates welcome)
Salary: β¬4,000 β β¬6,000 gross/month (Market rate based on experience)
Employment: Full-time | Start: ASAP
Language: English B1+ (Confident conversational level required)
About the Project:
We are building a next-generation AI & Data Platform that combines modern analytics with Generative AI. You will work on integrating LLMs, RAG architectures, and agent-based solutions into robust data pipelines, enabling real-time insights and intelligent automation.
Tech Stack & Requirements:
Must Have:
β’ Role: Proven experience as BI Engineer, Analytics Engineer, or Senior Data Analyst.
β’ SQL: Advanced proficiency (complex queries, optimization, window functions).
β’ Databases: Hands-on experience with PostgreSQL, ClickHouse, and/or TimescaleDB.
β’ BI Tools: Experience building dashboards and reports (Apache Superset is a priority).
β’ Data Integration: Strong understanding of ETL/ELT processes; experience with Apache NiFi (or similar tools like Airflow/dbt).
β’ Communication: Confident English for daily collaboration with international teams.
Nice to Have:
β’ Python: Scripting for data analysis (pandas, polars, pyarrow).
β’ ML/AI Context: Understanding of ML pipelines and how to serve models.
β’ Cloud Storage: Experience with AWS S3 or equivalent object storage.
β’ Real-Time: Knowledge of streaming analytics and event-driven architectures.
β’ AI Stack Familiarity: Basic understanding of LLMs, RAG patterns, LangChain/LangGraph, and Vector DBs (e.g., Qdrant).
What You'll Do:
- Design and maintain scalable data models in PostgreSQL/ClickHouse/TimescaleDB.
- Build interactive dashboards and self-service analytics using Apache Superset.
- Develop and optimize ETL/ELT pipelines (using Apache NiFi) to ingest data from various sources.
- Collaborate with Data Scientists and AI Engineers to integrate LLM/RAG outputs into analytical workflows.
- Ensure data quality, consistency, and performance across the platform.
How to Apply:
To apply, please fill out the candidate form:
#BIEngineer #AnalyticsEngineer #DataPlatform #SQL #ClickHouse #Superset #NiFi #AI #LLM #RemoteJobs #Hiring #DataEngineering
ΠΡΠ΄ΡΡΠ΅ ΠΎΡΡΠΎΡΠΎΠΆΠ½Ρ: Π΅ΡΠ»ΠΈ ΡΠ°Π±ΠΎΡΠΎΠ΄Π°ΡΠ΅Π»Ρ ΠΏΡΠΎΡΠΈΡ Π²ΠΎΠΉΡΠΈ Π² ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ iCloud/Google, ΠΏΡΠΈΡΠ»Π°ΡΡ ΠΊΠΎΠ΄/ΠΏΠ°ΡΠΎΠ»Ρ, Π·Π°ΠΏΡΡΡΠΈΡΡ ΠΊΠΎΠ΄/ΠΠ, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡΠ΅ ΡΡΠΎΠ³ΠΎ - ΡΡΠΎ ΠΌΠΎΡΠ΅Π½Π½ΠΈΠΊΠΈ. ΠΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎ ΠΆΠΌΠΈΡΠ΅ "ΠΠΎΠΆΠ°Π»ΠΎΠ²Π°ΡΡΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡΠΈΡΠ΅ Π² ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΡ. ΠΠΎΠ΄ΡΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β
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