Alex L.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.

I'm a senior engineer specializing in AWS data platforms and large-scale ingestion-to-query pipelines. My strongest ground is the S3-lakehouse + Spark stack — Glue, Athena, S3, Spark/PySpark — with Python and C#/.NET on the engineering side. I build systems that take data from raw web-scale ingestion to a partitioned, queryable dataset with seconds-level search latency, while keeping infrastructure costs under control through fully automated, ephemeral environments. RECENT PROJECT — web-scale data platform on AWS (built solo) - Built a large-scale website crawler in .NET 8 (C#) for link scraping / acquisition - Ran it across thousands of ephemeral Kubernetes pods on EKS (Kubernetes Jobs + SQS), high-throughput distributed execution - Stored terabytes of crawl output in S3 (Parquet/Snappy) - Built AWS Glue (PySpark) pipelines producing a well-partitioned dataset of billions of records - Used Delta Lake for incremental updates (upserts/merges) as new crawls arrived - Exposed the dataset via Athena + a SAM-based GraphQL backend, enabling search in seconds - Automated the full workflow with Terraform + CodeBuild + Step Functions: provision EKS → crawl → process → publish → teardown, to control cost - Reliability throughout: idempotency, retry logic, monitoring (CloudWatch) WHAT I CAN DO FOR YOU - Glue / Athena / S3 lakehouse: partitioning, file sizing, performance + cost tuning, large-scale ETL/ELT - Spark / PySpark: large-scale batch processing, partitioned datasets at billions of records - EKS / Kubernetes: batch workloads, orchestration patterns, operational automation - Serverless + query layer: Lambda + SAM, fast query endpoints over Athena - End-to-end pipelines: ingestion → processing → query/API, with monitoring and failure recovery - Also hands-on with: Terraform, Step Functions, CodeBuild, Delta Lake (incremental upserts/MERGE), GraphQL, DynamoDB AI-AUGMENTED ENGINEERING I build LLM-powered and agentic workflows (structured extraction, schema validation, scheduled agents) and develop with AI tooling (Claude Code, Cursor) TECH STACK - AWS (core): Glue, Athena, S3, EKS, Lambda, SAM, EC2, SQS, SNS, CloudWatch - Data: Spark/PySpark, large-scale ETL/ELT, partitioned datasets, Parquet, SQL - Languages: Python, C#/.NET, Scala - Backend: ASP.NET Core (REST) - Also used: Terraform, Step Functions, CodeBuild, Delta Lake, GraphQL, DynamoDB, Kubernetes, Docker AWS Solutions Architect – Associate (in progress) Availability: 100% remote · CET time zone · up to 40 h/week · short notice.