A dedicated Data Engineer with a strong background in Software Architecture and Microservices, focused on building scalable, reliable, and high-performance data systems.
I specialize in transforming complex datasets into actionable insights using modern open-source technologies such as ClickHouse, Polars, DuckDB, and Kafka — all while ensuring data quality, observability, and performance.

Over 5 years of hands-on experience designing and implementing end-to-end data platforms, from ingestion and orchestration to serving APIs.
Currently contributing to market-surveillance and real-time analytics systems at Iran FaraBourse (IFB) and leading data architecture design at a BioTech startup in Sweden.

• Data ingestion & transformation (ETL/ELT) using Prefect, Airflow, MageAI
• Real-time & streaming pipelines with Kafka, Redpanda, and ClickHouse
• DataLakehouse architecture with Iceberg, DuckLake, MinIO (S3)
• Advanced analytics using Polars, DuckDB, and Apache Arrow

• FastAPI, gRPC, AsyncIO, Celery for high-performance APIs
• Designed an internal FaaS platform at IFB for dynamic, scalable gRPC endpoints
• Experience with distributed systems and event-driven design

• Built real-time data quality monitoring with Prometheus, Grafana, and OpenTelemetry
• Implemented unified logging and metrics systems across multiple data services

• ClickHouse, PostgreSQL, MongoDB, Neo4j, Qdrant, Elasticsearch
• Schema design, indexing strategies, and query optimization for OLAP/OLTP workloads

• Integration of LangChain and OpenAI for document embedding and semantic search
• Built vector search pipelines using Qdrant (768D cosine embeddings)
• Designed microservices for LLM-powered analytics and biomedical knowledge graphs

Jan 2025 – Present

• Designed full data & analytics workflows using DuckDB, Polars & Apache Arrow
• Modeled a biomedical knowledge graph in Neo4j and implemented vector search with Qdrant
• Developed a gRPC microservice exposing vector retrieval and search APIs

Oct 2024 – Present

• Built in-house FaaS platform with dynamic gRPC endpoints serving 5+ internal systems
• Refactored 10+ Prefect pipelines, improving reliability from 85% → 99.9%
• Migrated analytical schemas to ClickHouse, achieving 40% faster queries

Sep 2023 – Dec 2024

• Built ETL/data pipelines with Apache Airflow & MageAI
• Deployed PostgreSQL-based warehouse cutting analytics cost by 30%
• Developed data quality monitoring via Prometheus + Grafana

Sep 2023 – Jan 2024

• Refactored pipelines to reduce latency and improve I/O throughput
• Designed gRPC + SQS integrations for data flow between services

May 2023 – Sep 2023

• Built ingestion pipelines reducing data lag by 2 hours
• Used Azure OpenAI to generate SWOT analyses from embedded documents

Aug 2021 – May 2023

• Developed trading assistant (Atlas) using Kafka & PostgreSQL
• Reduced validation time by 40%, enabling low-latency trading insights

Languages: Python, SQL, Shell, Rust (Intermediate)
Frameworks: FastAPI, gRPC, AsyncIO, Celery
Data Tools: ClickHouse, Kafka, DuckDB, Polars, Prefect, Airflow, MageAI
Storage & Lakehouse: MinIO, Iceberg, DuckLake, Dremio, Nessie
Databases: PostgreSQL, MongoDB, Neo4j, Qdrant, Elasticsearch
Monitoring: Prometheus, Grafana, OpenTelemetry
DevOps: Docker, GitHub Actions, GitLab CI, Kubernetes
Visualization: Metabase, Superset, Grafana

• 🎓 Dremio Verified Lakehouse Associate
• 🧱 Data Engineering Essentials
• 🌀 ETL and Data Pipelines with Shell, Airflow, and Kafka
• 🗃️ Relational Database Administration Essentials
• 🐍 Python Project for Data Engineering
• 🧮 LangChain for LLM Application Development

Bachelor’s Degree in Software Engineering
Islamic Azad University (2014 – 2018) | GPA: 3.05/4.0

📊 “Data without context is noise — my mission is to turn that noise into signal.”