Damian Skrzypiec

• Core ConnectyAI Backend in Go
  • Design and implementation of REST API endpoints
  • Developing core product features: Optimization Guides, Business Goal resolution (DAG-based), Dashboards, and a cron-based Workflow scheduler
  • Implementing permissions system, org plan management, and Auth0 M2M public API
  • Integrations with AI agents
• Implementing data connectors for multiple warehouse types
  • Full support for BigQuery, Snowflake, Postgres, AWS Athena, Databricks, and AWS Redshift
  • Object listing, column listing, data sampling, statistics, and query history per connector
  • Postgres-based concurrency limiter with FIFO fairness for rate-limiting client connections
• Building and maintaining data sync infrastructure
  • Day-0 sync process, catalog sync, and Query History sync pipeline
  • Event-driven Events Processor on AWS Lambda + SQS with progress tracking
  • Virtual Objects/Columns detection and cross-workspace enrichment copying
• Infrastructure using AWS CDK
  • Migration of Aurora PostgreSQL clusters to encrypted instances using DMS and pg_restore
  • Setup and maintenance of ECS services, Lambda functions, SES, and bastion hosts

• Developing new distributed platform for computation and analytics for Risk team in Point72
  • Developing and maintaining platform infrastructure based on Ray and AWS EKS
  • Developing core Python library which is a gateway to the new platform
  • Implementing Ray actors life cycle management
  • Working on performance improvement of the platform
• Introducing Apache Airflow as a new scheduler in Risk Tech using AWS MWAA
  • Setup MWAA infrastructure via Terraform
  • Setup integration with other internal systems — SQL Server and Ray cluster on AWS EKS
  • Implement customized local setup of Airflow using Docker
  • Implement ETL processes preparing data for the new platform, using Airflow DAGs
  • Design the release process and CI/CD pipelines

• Developing Overseas Big Data Platform for TCL
  • Development and maintenance of data pipelines — Spark (Scala) with AWS Glue jobs
  • Development and maintenance of AWS infrastructure (8 global regions) using AWS CDK with TypeScript
• Performing infrastructure code migration from AWS CDK v1 into AWS CDK v2
• Maintenance of tracking platform which handles events in real-time using data mesh-like approach
• Development of cross-cloud ETLs — AWS to AWS China and AWS to Alibaba Cloud (Aliyun)
• Development of end-to-end tests for Spark (Scala) transformations
• Development and maintenance of AWS Lambda in Python

• Backend implementation of a web app in Go
  • Implementation of user authentication and authorization
  • Implementing login using OAuth2
• Design and implementation of ETL process for integrating third-party database serialization
  • Loading from AWS S3 into Go program inside AWS Lambda with asynchronous writes into AWS Aurora
• Implementation of a search engine using combination of internal database and external HTTP API
• Implementation of communication between backend and frontend using WebSocket protocol

• Maintenance of the core analytical databases (Snowflake)
• Design and implementation of data pipelines (Apache Airflow)
• Design and implementation of the process for loan evaluation
  • Set up Google Composer infrastructure
  • Design data model schema
  • Implementation of Apache Airflow DAGs for the process
  • Design reporting and communication with other processes
• Consult and review of C# services regarding data models and Snowflake
• Implementation of analytical data model based on technical events using Snowflake and dbt
• Integration of all historical data on delivery addresses from Cassandra and MongoDB into Snowflake using Go

• Maintenance and development of an IFRS 9 application for an international bank
  • Implementation of new features on the backend (C# and SQL Server)
  • Improvement of the key processes of the application
  • Development of end-to-end tests
  • Development of CI/CD processes (TeamCity and Octopus)
• Implementation of .NET Core backend prototypes for web apps
• Guiding and performing code reviews for junior devs

• Design and implementation of an application for credit risk models validation
  • Designing the application database schema (SQL Server)
  • Backend implementation (HTTP server in Go)
  • Communication with analytic layer (R) and the frontend (Angular)
• Design and implementation of an IFRS 9 application for a factoring company
  • Managing a four-people team
  • Designing the database (SQLite)
  • Implementation of estimation, calculation and reporting layer
• Design and implementation of tools (R) for building behavioral models in market risk
• Internal workshops — Go language (8h)

• Designing and leading development of internal tools for modelling
• Implementation of automation estimation of parameters for credit risk models
• Implementation of calculation stress tests for expected credit loss
  • Designing the database schema (SQL Server)
  • High performance calculation engine in Go
  • Communication with analytical layer (R)
• Testing (unit and end-to-end) monolith IFRS 9 (C#) application
• Internal workshops — git (2h), R (20h) and an introduction to HTTP protocol (2h)

• Building and implementing models for credit risk
• Use machine learning to improve parts of credit risk models
• Algorithms performance optimization (C# and T-SQL)
• Data analysis, reporting and validations (R)

• Developing a prototype of real-time application using geodata of clients (R, Shiny)
• Developing an application in VBA for periodical reports with data visualization and stats