1. Data Platform (IoT) for a maritime companyLead platform refactoring for over 2TB data, construct real-time analytics.Key Achievements:• Led the refactoring of the existing data platform, migrating to the cloud, managing a substantial volume.• Constructed a robust data platform for analytics, continuous monitoring, and real-time processing with both real-time and batch data pipelines.• Deployed ML models within the platform to detect anomalies in devices, enhancing predictive maintenance capabilities.Stack: GCP, Apache Beam, Google Pub/Sub, Google Composer, BigQuery, Python, Java, GKE, Terraform2. Data Platform (IoT) for a green energy companyLead data platform development for analytics and real-time insights.Key Achievements:• Built a data platform for analytical and continuous monitoring purposes, managing over 10TB of metering data.• Developed real-time data pipelines, ensuring timely processing of metering data for actionable insights.• Implemented data lake improvements to enhance storage and retrieval efficiency.Stack: Azure, Databricks, Apache Flink, Azure Event Hub, Python, Java, Terraform, Kubernetes

Led and managed teams of Data Engineers and DataOps, fostering a collaborative work environment.Key Achievements:• Successfully built and maintained a horizontally scalable Data Platform handling approximately 20 TB of data.• Enriched the Data Platform with real-time streaming from internal databases and batch loading from external APIs.• Implemented metadata storage for table dependencies and documentation, enhancing data traceability.• Provided seamless data and infrastructure support to ML Engineers, DaaS Developers, and Analysts through datamarts.• Formulated a vision and strategy for the Data Platform, contributing to the overall success of the organization.Stack: BigQuery, Airflow, Datahub, Debezium, Pub/Sub, Kafka, Apache Beam, Dataflow, Kubernetes

Led and managed a team of Data Engineers, fostering collaboration and achieving project goals.Key Achievements:• Enriched the Data Platform, enhancing its capabilities for the Marketing Department.• Successfully refactored the Data Platform for improved efficiency in the Marketing Department.• Formulated a vision and strategy for the Data Platform, aligning with organisational objectives.• Effectively managed backlog, ensuring timely project delivery.• Maintained the Data Platform infrastructure to guarantee optimal performance.Stack: BigQuery, Airflow, Pub/Sub, Dataflow, Datahub

As the Product Owner, led a cross-functional team to maintain a Data Platform, develop and maintain internal data products.Key achievements:• Maintained a top-ranking Vertica installation in Russia, handling clickstream data at a rate of ~15 billion events per day (40TB/day).• Played a pivotal role in the successful development and maintenance of internal products.• Formulated a clear product vision and strategy, aligning with stakeholder needs and company objectives.• Managed a backlog effectively, ensuring the timely delivery of data products to over 100 users.Stack: Vertica, Kafka, Debezium, Airflow, Redis, Sqitch

Collaboration with Data AnalystsKey Achievements:• Introduced BigQuery• Introduced Airflow• ETL developmentStack: Airflow, BigQuery, Spark, PostgreSQL

Key achievements:• Built an ML model to optimize the work of the customer center (WFM)• Managed a small group of analysts• Automated data collection and analysis• Automated reporting systemStack: Python, Vertica, PostgreSQL, Tableau