• Actively engaged in day-to-day development and cloud infrastructure tasks, ensuring hands-on involvement and oversight.• Led software engineering management, overseeing the entire development lifecycle.• Cultivated and managed a high-caliber technical talent pool.• Designed and executed effective technical talent-hiring and interview processes.• Orchestrated internal software architecture and development processes.• Upheld a robust DevOps culture and software development best practices.

• Designed, developed, and deployed efficient data infrastructures, ETL/ELT processes on Google Cloud, AWS, and self-managed data platforms.• Experienced with both streaming and batch analytics. Implemented Lambda and Kappa Architectures.• Designed Data Warehouses (Kimball’s dimensional model), Data Lakes, and Data Lakehouses with Medallion architecture. • Implemented approaches to ensure and monitor data quality, data lineage, and data provenance.• Consulted and guided implementation of DataOps and MLOps practices in teams of data engineers and data scientists.• Designed and developed CI/CD pipelines using GitHub Actions and Jenkins.• Performed Platform Engineering with Kubernetes and CNCF stack for cloud, hybrid cloud, and on-premise environments.• Guided initiatives to improve developer productivity using DORA metrics, shift-left testing, and GitOps practices.• Developed REST APIs, microservices, authentication flows, and CLI automation tools.

• Led agile and focused team of dozens highly skilled engineers and consultants.• Involved in technical sales and presales, as well as software and cloud architecture development.• Operated in various areas of development and consulting, with a primary focus on DevOps and Cloud Infrastructure Engineering, Data Science and Data Engineering, and Software Testing Automation.

• Toptal core team member at Data Engineering and Data Science team.• Designed, developed and maintained high-performance ETL/data processing and data analytics solutions, data warehouses, data lakes.• Designed and developed software for data quality, data observability, and data lineage.• Leveraged Data Science/ML for internal data analysis and making a prediction based ondata.• Developed internal KPI and metrics for individual/team-based performance monitoring.• Maintained the stability of GCP (Google Cloud Platform) data infrastructure and troubleshoot data pipeline issues to minimize ”data downtime”.

• Developed Big Data solutions using Apache Hadoop and Apache Spark, resulting in improved data processing efficiency and scalability.• Applied machine learning algorithms, particularly XGBoost, to enhance predictive modeling and decision-making processes.• Conducted comprehensive data analysis using Python, Pandas, and Jupyter Notebooks, delivering actionable insights to stakeholders.• Collaborated with cross-functional teams to ensure seamless integration of Cloudera and Hortonworks platforms into existing workflows.

• Led the design and implementation of databases on the Microsoft SQL Server Platform, optimizing performance and ensuring data integrity.• Developed and maintained ETL processes using SSIS and T-SQL, enhancing data flow and integration across systems.