
Sergey Dmitriev
Verified Expert in Engineering
Software Architect and Developer
Seattle, United States
Toptal member since June 18, 2020
Sergey is a senior data management professional, solution architect, and cloud architect with over 20 years of experience developing data-intense applications as well as building and leading technical teams to successfully deliver challenging software development and migration projects. Sergey is skilled in all aspects of software design and development with demonstrated expertise in application delivery planning, design, and development.
Portfolio
Experience
- ETL - 20 years
- Data Integration - 20 years
- SQL - 20 years
- Software Architecture - 10 years
- Python - 6 years
- Snowflake - 5 years
- PySpark - 5 years
- Databricks - 3 years
Availability
Preferred Environment
Amazon Web Services (AWS), Google Cloud Platform (GCP), Spark, PySpark, Python, Apache Hive, Databricks, Snowflake, Apache Airflow, Fivetran
The most amazing...
...project I've completed involved anomaly detection for an authorization service (Facebook, data infrastructure security).
Work Experience
Staff Data Engineer
Dropbox
- Implemented a reliable integration with Google Ads Services.
- Migrated data pipelines from a legacy platform to Spark and Airflow.
- Consolidated legacy data platform elements into a strategic one.
Staff Data Engineer
- Built an anomaly detection platform for a data platform authorization service.
- Implemented infrastructure analytics for real-time communication between Instagram and Messenger.
- Created a unified analytics platform for operational health monitoring for real-time communication products.
Senior Back-end Engineer
Gradient
- Built a data platform to ingest and process data from different sources.
- Created data pipelines for Power BI analytics and ML algorithms.
- Constructed a monitoring and alerting tool to simplify data platform operations.
Lead Solution Architect of Data Platforms
Amazon Web Services
- Planned and implemented relational database migrations to AWS.
- Designed and implemented data warehouses, data lakes, and operational data stores in AWS.
- Designed and implemented data pipelines on AWS using SQL and Python.
- Created data models and database components for databases (Oracle) hosted on AWS RDS and EC2.
- Optimized the performance of reports and SQL queries for databases (Oracle) hosted in AWS.
- Created labs, sales demos, and conference activities for database migrations to AWS.
Lead Data Architect
Deutsche Bank
- Consolidated legacy Oracle databases (up to 100TB in size) on an Exadata which included merging models and data, migrating data, and modifying PL/SQL, Shell, and Java code.
- Optimized the performance for reporting components on Exadata from hours-long running time to seconds.
- Created data model and database components (Oracle) for an application managing a lifecycle of listed derivatives transactions (2,000 transactions per second).
- Designed and implemented a data model and database code for a risk management platform to capture risk model parameters for every risk calculation for compliance reporting.
- Designed and implemented a dynamically configured reporting engine (in PL/SQL) for processing a 30TB dataset.
- Designed and implemented a data model and database code for a real-time warehouse for the sales IT department, receiving information from 150+ feeds, and applying complicated logic to calculate sales commissions.
Senior Database Developer | Database Administrator
INIT-S
- Designed and developed document management systems and resource management systems for nuclear power plants to manage each power plant’s entire documentation process.
- Enhanced and automated resource management, performed database migration between different platforms (Sybase ASE, MS SQL Server, Oracle), database server administration, deployment packages creation, and consulting customers.
- Migrated critical databases from Sybase ASE to Oracle.
Experience
Transformation Program for a Core Banking Equity Settlement Application
Data Pipelines on Google Compute Cloud
Data Pipelines on AWS
My Python experience includes building data pipelines for data warehouses and data science projects. I've also built on-premises and cloud data pipelines as well as back-end serverless cloud APIs on AWS.
I've used also Spark to compute intense data pipelines in batch mode and Spark SQL so I'm very comfortable working with Spark and will learn new use cases quickly.
Anomaly Detection for Data Platform Access Authorization
Infrastructure Analytics for a Real-time Communication Platform
Education
Master's Degree in Computer Science
Moscow Power Engineering Institute - Moscow, Russia
Certifications
AWS Certified Solution Architect - Associate
AWS
Oracle Certified Professional (DBA)
Oracle
Skills
Libraries/APIs
PySpark, Pandas
Tools
Apache Airflow, Erwin, Oracle Exadata, Spark SQL, Amazon Elastic MapReduce (EMR), AWS CloudFormation, Git, Tableau
Languages
SQL, Snowflake, Python, COBOL
Frameworks
Presto, Spark, Hadoop, Apache Thrift
Paradigms
Database Development, ETL, Database Design
Platforms
Oracle, Amazon Web Services (AWS), Databricks, Google Cloud Platform (GCP), Amazon EC2, Linux, Apache Pig
Storage
Relational Databases, Databases, Oracle RDBMS, Redshift, Amazon S3 (AWS S3), Data Integration, Apache Hive, Amazon Aurora, Google Cloud, PostgreSQL
Other
Data Modeling, Shell Scripting, Google BigQuery, Software Design, Software Architecture, Amazon RDS
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