Muhammad S.Private profile: Upwork shows its earnings only to signed-in members, so we check it every few weeks, not daily. MRR here is a rough estimate (Upwork's six-month earnings ÷ months active). Last read Nov 5, 2026.

Top Rated Plus, 100% Job Success, $40K+ earned building real-time Kafka pipelines for SaaS and fintech, plus ClickHouse, Snowflake and dbt - the systems that keep a business running, built to hold up at scale. Three things usually break first: analytics queries competing with production traffic on the same database, batch reporting that used to be fast enough and now isn't, and an AI layer bolted onto data nobody trusts. I fix them in that order - stabilize the data path first, then speed it up, then put AI on top of something solid enough to hold it. REAL-TIME & STREAMING DATA PLATFORMS Change data capture into Kafka, streaming into ClickHouse or Snowflake, with schema changes propagating automatically instead of breaking the pipeline. This is where most of my client work sits: replacing "run the report overnight" with "the number is already right." AI SYSTEMS AND AUTOMATION Agents and RAG knowledge bases built on top of the data platform, not next to it - so the AI is reasoning over numbers that are actually current. Automation that pulls from messy sources, reasons with an LLM, and produces a finished output end to end, not a draft that still needs cleanup. DATA WAREHOUSING AND ETL dbt and Airflow-orchestrated warehouses on Snowflake and BigQuery, ELT pipelines via Fivetran and Airbyte, and the unglamorous work of migrating a warehouse without losing rows or breaking the dashboards built on top of it. RECENT WORK Market4You: MySQL binlog into Kafka, streaming into ClickHouse with sub-second query response. Automated schema mapping propagates new production columns without manual migration, so loyalty and GMV reporting update within seconds. Python, Docker, GitLab CI/CD. Venon: CDC-to-Kafka-to-ClickHouse pipeline across 27 raw tables, mart models refreshing every five minutes, migrated onto Kubernetes with zero rows lost and zero downtime. Current engagement: an ongoing, multi-hundred-hour Senior Data Engineer role on Snowflake, AWS and Airflow. Clients range from a forex/CFD brokerage running a multi-year managed real-time platform to venture-backed startups building their first real data backbone. If you're building a real-time data platform, an AI system that needs to sit on real data, or scaling pipelines that have started to hurt - send me your current setup and I'll tell you what I'd change first, and why. As-needed availability, 0-4 hour response time, open to contract-to-hire. Keywords: Data Engineering, Real-Time Data Pipeline, Kafka, CDC, ClickHouse, Snowflake, BigQuery, dbt, Airflow, Dagster, ETL, ELT, Data Warehousing, Data Modeling, Streaming, Fivetran, Airbyte, PostgreSQL, Python, SQL, AWS, GCP, Docker, Kubernetes, RAG, AI Automation