Sergey Kham Email & Phone Number

Vancouver, British Columbia, Canada

Moscow, Russian Federation

- Created 4+ data marts which helped other teams to earn more than 10M+ in revenue.- Built 10+ batch/streaming data pipelines with Scala/Python, SQL, Spark, Airflow, Flink and Kafka -> processed 5+ TB daily- Communicated with Data Scientists, Business Analysts, QA and DevOps Engineers while building data pipelines- Created and maintained a Python library called EasyDag, which helped to build DAGs in Airflow without aboilerplate code. Every data engineer in my team used it in their everyday work while creating data pipelines.- Migrated 40+ pipelines from Airflow v 1.10.9 to v.2.1.4 in K8s and presented our approach to 90+ employees in our department.

Team management of data engineers:- Planning tasks with internal customers: project and product managers- Implementing of technical task realization plans- Coordinating work of the team and curating of incoming questions- Reviewing code and validating task results- Performing administrative tasks: team’s vacation planning, management of the team’s working hours, tracking progress of tasks: writing comments and creating tasks descriptions- Hiring and training new data engineers- Educating the team on best practicesWork with big data:- Databases architecture: Creating database models depending on a specific task- ETL task automatization: Apache Airflow, Jenkins- Python/Scala/ETL: Processing huge amounts of raw data in Python/Scala, transforming data into required formats and creating/updating data warehouses for further usage of business analysts/project or product managers - AWS EMR/Spark/Zeppelin: Creating and configuring AWS EMR clusters, using Spark for parallel data processing and Zeppelin for fast solving of ad-hoc tasks- Kibana: Monitoring the work of data pipelines- SQL: Writing/reviewing/editing SQL queries (Presto) in AWS AthenaDocumentation:- Describing configuration of inner data warehouses: schemas, data examples, potential anomalies and code snippets- Writing instructions for using created tools and conducting necessary training for employees- Creating code snippets for data processing and transforming

Moscow, Russian Federation

Team management of data engineers:- Planning and statement of tasks with internal customers: project and product managers- Implementation of technical task realization plan- Coordinating the work of the team and curating of all incoming questions- Code reviewing and validation of tasks resultsWork with big data:- Python/Scala/ETL: Processing huge amount of raw data in Python/Scala, transforming data into required formats and creating/updating data warehouses for further usage of business analysts/project or product managers - AWS EMR/Spark/Zeppelin: Creating and configuring of AWS EMR clusters, using Spark for parallel data processing and Zeppelin for fast solving of ad-hoc tasks- Kibana: Monitoring the work of data pipelines- SQL: writing/reviewing/editing SQL queries (Presto) in AWS Athena

- Writing Python scripts for automatizing tasks of business analysts- Writing Python code using nternal and external APIs- Using inner data warehouses- Monitoring data quality with Kibana - Processing and analyzing raw data

- Data structuring in a tabular form- Manually adding data to a database- Working with Python scripts- Analyzing business needs and writing tasks for data engineers

- Preparation of commercial proposals- Scheduling appointments and holding meetings with clients- Acquiring new customers and closing deals- Working with cold / warm customer base

Bachelor'S Degree, Philosophy

Bachelor'S Degree, Business Administration And Management, General

Bachelor'S Degree, Computer Science