Oleg B.

Oleg B. — ML Engineer/Big Data Architect

Expertise in Data Engineer.

Last verified on August 05, 2023

Core Skills

Bio Summary

- Over 15 years experience in leading the design, developing, and delivery of complex IT projects and high-performance solutions, +10 years in business intelligence and in the data analytics field - Advanced hands-on experience in reactive, microservices-based, distributed system design and development including stream application platforms for advanced analytics including machine learning and data science - Proficient Data Engineer-researcher focused on the immediate benefits for the business using Big Data tools (AWS Glue, AWS Greengrass, AWS EMR, AWS Data Lake) with advanced analytical and visualization APIs (graph DB – Titan, Neo4J, Tinkerpop, software development – Scala, Python) with CI/CD pipelines – Jenkins, Circle CI, GitLab actions - Generative AI - Q&A with multiple choices, pre-trained models (Hugging Faces ecosystem, T5, BERT, GPT), ChatBot for online gambling platform (LangChain, Pinecone, Cohere, Faiss, Hugging Face Hub) - Generative AI in NLP - information retrieval for 1) generate personalized recommendations for products or services based on a user's preferences and past behavior 2) summarize legal documents and contracts, making it easier for lawyers and legal professionals to review and analyze large volumes of legal documents. 3) create content such as product descriptions, blog posts, and social media posts - Recommendations platforms - mobile games platform (generate game recommendations based on player history, promo-offers, AWS Personalize ), self-learning algorithms for data-based risk management in agriculture (Monte-Carlo tree and Markov chains) - Upper-intermediate English. - Availability starting from ASAP

Technical Skills

Programming Languages	Python, R, Scala
Scala Frameworks	Akka, Apache Spark
Scala Libraries and Tools	Akka
Java Frameworks	Apache Spark
AI & Machine Learning	AWS SageMaker (Amazon SageMaker), Keras, Kubeflow, Mlflow, PyTorch, TensorFlow
.NET Platform	Azure
Python Libraries and Tools	BentoML, Dask, Keras, Matplotlob, Metaflow, Pandas, PyTorch, Seaborn, TensorFlow
Python Frameworks	Django
Data Analysis and Visualization Technologies	Apache Airflow, Apache Hive, Apache Spark, HBase, Jupyter Notebook, ML, Pandas, Power BI, Sqoop
Databases & Management Systems / ORM	Apache Hadoop, Apache Hive, Apache Kylin, Apache Spark, AWS ElasticSearch, AWS Redshift, Cassandra, ELK stack (Elasticsearch, Logstash, Kibana), Microsoft SQL Server, MongoDB, MySQL, Neo4j, Oracle Database, PostgreSQL, Redis, Snowflake, SQL
Cloud Platforms, Services & Computing	AWS, Azure, Azure ML, GCP
Amazon Web Services	AWS EC2, AWS ElasticSearch, AWS Glue, AWS Kinesis, AWS Lambda, AWS RDS (Amazon Relational Database Service), AWS Redshift, AWS S3, AWS SageMaker (Amazon SageMaker), AWS SAM, AWS VPC
Deployment, CI/CD & Administration	Ansible, CI/CD, Helm
Web/App Servers, Middleware	Apache HTTP Server
Platforms	Apache Mesos
SDK / API and Integrations	API
Mail / Network Protocols / Data transfer	Consul
Operating Systems	Debian, Linux, Ubuntu, Windows
Virtualization, Containers and Orchestration	Docker, Kubernetes, Terraform
Version Control	Git
Collaboration, Task & Issue Tracking	Jira, Redmine
Message/Queue/Task Brokers	Kafka
Other Technical Skills	Hashicorp, Pachyderm, Raspberry

Experience

Data Engineer

September 2021 - now

ML Engineer

April 2020 - now

ML Engineer

March 2018 – April 2020

Data Engineer, Scotiabank Digital Factory

September 2017 – March 2018

Big Data Architect, ACCENTURE UKI

June 2016 - August 2017

Data Scientist, Canadian Tire Corporation

August 2015 – June 2016

Big Data Engineer, RAYTM LABS

December 2014 – July 2015

Data Science Developer, KINROSS

July 2008 - February 2015

Projects

Big Data Developer / Data Engineer

Nov 2022 - now
Description: Data Engineer for Palantir Foundry
Responsibilities: Design and development ETL pipelines (process flows) and models based on Palantir Ontology and Apache Spark to handle structure batch data. Using Palantir API to connect different data sources to the corporate data lake
Technologies: Palantir Foundry (PySpark)

Data Engineer

Jun 2022 – Nov 2022
Description: A platform for online tests, Q&A
Responsibilities: Design and development AWS-based ETL pipelines to handle structured and unstructured data for online assessment and educational platforms. Setup and configuration of AWS data like using Databricks platform and Apache Spark Platform performance analysis and troubleshooting. POC for Online assistant leveraging NLP algorithms (PyTorcn, Transformers). Ingestion pipelines (based on AWS GLue + Data Catalog), developing Redshift Db data models( dist keys and sort keys)
Project link: https://www.inspera.com/
Technologies: AWS S3, Lambda, Glue, Redshift, Step functions, Databricks Live tables (Delta lake), ElasticSearch, powerBI

Data Engineer

Jan 2022 – Jun 2022
Description: One of the biggest airline companies in the world
Responsibilities: Providing high-quality, professional services to help organizations establish a data-driven company that treats data as a strategic asset. Delivering innovation projects in a variety of business areas including Enhance Capabilities, Quality Management, DevOps implementation, Innovation model, and Integrated portfolio based on ground-breaking Big Data, Machine Learning, and AI technologies and frameworks. Active participation in the creation of Big Data CoE as the One-Stop Shop. Developing ML models for credit risk management. Implementation data science platform to predict the contingency fuel required for a given flight considering the influencing factors. Advanced Exploration Analysis applied to short-term and long-term planning. Automatic forecast analysis
Technologies: AWS, Google Cloud, Apache Spark, Apache Mesos, Cassandra, Kafka, Hive, Zeppelin, Jupyter, Scala, Python, TensorFlow, PowerBI

Big Data Engineer

Sep 2021 – Jan 2022
Description: Bank which offers personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets, through its global team
Responsibilities:

Integration Big Data technology stack and machine learning models via microservices architecture

Technologies: Google Cloud, Apache Spark, Apache Mesos, Cassandra, Kafka, HDP 2.3, Teradata Aster, Zeppelin, Jupyter, Scala, Python, Keras, R, PowerBI

Data Engineer

Sep 2017 – Mar 2018
Description: Information Management Architecture Strategy (IMAS) in Nationwide Building Society
Responsibilities:

Implementation of Discovery Analytics / Data Science stream including Full-scale machine learning techniques across multiple environments - Path Analysis (nPath), Attribution Modelling, Naïve Bayes (analyze behavioral differences), Cluster Analysis (to identify key investor types, segmentation), Text Analytics (n-gram) for key trigger phrases from the text, Graph analytics for analysis of process steps actually taken in member web journeys, Time series analysis for periodicity detection. Ingestion pipelines (based on AWS GLue + Data Catalog), developing Redshift Db data models( dist keys and sort keys)

Technologies: AWS (Glue, Redshift, etc), Google Cloud, Apache Spark, Apache Mesos, Cassandra, Kafka, Hive, HDP 2.3, Teradata Aster, Apache Solr, Zeppelin, Jupyter, Scala, Python, TensorFlow, Keras, R

Data Engineer

Jun 2016 – Aug 2017
Description: A corporation, one of the leaders in the retail industry in Canada, owning a network of stores in all provinces and territories of the country
Responsibilities:

Developing and implementing of multi-layer threat / linked data analysis platform hosted in a Big Data environment. Design and modeling Security Data Lake (HDFS, Avro, Parquet, HBase, Cassandra) Identification and importance analysis of  behavioral features for network/users Anomaly Detection (SIEM, CarbonBlack, FireEye, AVT, firewalls, etc). Data cleaning and enriched representations for Anomaly Detection in system calls (R, Scala). Implementation of a combined approach for anomaly detection using neural networks (SOM) and unsupervised clustering techniques (R, Scala, Python). Developing the hybrid malicious code detection method based on Deep Learning and the application of Deep learning on traffic identification (R, SparkR). Ingestion pipelines (based on AWS GLue + Data Catalog), developing Redshift Db data models( dist keys and sort keys)

Technologies: AWS (Glue, Redshift, etc), Google Cloud, Apache Spark, Apache NiFi, RabbitMQ, Cassandra, Kafka, Hive, HDP, ELK, Zeppelin, Jupyter, Scala, Python, R

Senior Big Data Engineer / Data Scientist

Aug 2015 – Jun 2016
Description: Fastest growing Indian e-commerce
Responsibilities:

Integration of Big Data technology stack

Technologies: AWS, Apache Spark, Apache Sqoop, RabbitMQ, Cassandra, Kafka, Hive, HDP, Zeppelin, Jupyter, Scala, Python, R

Data Engineer

Dec 2014 – Jul 2015
Description: One of the world's leading gold mining companies
Responsibilities:

Leads project teams. Worldwide implementation of MicroStrategy 9.3/4 and MicroStrategy Distribution services, OLAP Cubes, and MicroStrategy mobile across company sites in North and South Americas and Russia. Expertise in Installing, Configuring all MicroStrategy activities including MicroStrategy Desktop, Administrator, Intelligence Servers, Web Servers, and mapping to Client machines. Strong Knowledge of Data Extraction, Data Integration, and Data Mining for Decision Support Systems using ETL and OLAP tools. Intensive experience and exposure to all aspects of BI and data mining applications such as Administration, Architecting, and Development. Strong understanding of Data warehouse concepts, dimensional modeling using various Schemas and Multi-Dimensional Models with respect to query and analysis requirements

Technologies: Apache Hadoop, Sqoop, Hive, HBase, Visual.Net, MS SQL, SSIS, SSRS, SharePoint, C++, Java, C#, MicroStrategy 8-9

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