Nazarii Melnychuk

Senior Software Engineer

Major Points

• Senior Software Engineer with 9 years of experience in high-performance distributed systems and data pipelines
• Strong production experience with Python, Scala, Java, and Golang
• Expert in data processing tools (Apache Spark, Akka Streams)
• Track record of system optimization and technical leadership
• Technical interviewer and Scala bootcamp trainer

Specialized in

• Big Data solutions with Apache Spark for streaming and batch processing
• Scalable data pipelines using Scala, Python, Airflow, and AWS
• Relational DBs (PostgreSQL, MySQL) and warehouses (Amazon Redshift)
• Microservices architecture with Akka HTTP and Akka Streams

Leadership and mentoring

• Led technical evaluations and onboarding of engineers while being a Scala mentor within my team
• Delivered intensive Scala bootcamp lectures for recruiting and upskilling mid-to-senior engineers
• Conducted internal Scala workshops to enhance teams capabilities
• Facilitated cross-team collaboration to accelerate project delivery and customer value

Industry Experience

• Cloud communications (WhatsApp, RCS, SMS)
• Marketing/Adtech (user engagement data, ad analytics)
• Healthcare data processing and HIPAA compliance
• IoT monitoring for food/beverage companies
• Energy sector digital transformation

Achievements

Communications project

• Developed in-house services replacing costly external APIs, generating $100k-$250k customer savings
• Optimized message routing and billing pipeline during Kinesis-to-Kafka migration
• Achieved improved throughput (830+ MPS) by eliminating processing redundancies
• Implemented comprehensive cross-stream validation to ensure data consistency between source systems during this critical transition

Healthcare project

• Transformed legacy Python batch jobs into scalable Apache Spark workflows, successfully migrating complex healthcare data processing logic
• Contributed significant system architecture decisions across multiple projects to build production-grade ETL pipelines handling diverse healthcare data formats

Skills

Experience

October 2021 - Now

Messaging Project

Customer: US SaaS company

Developed core components of omnichannel messaging platform, enabling enterprise customers to reach users across WhatsApp Business, RCS, and SMS channels through unified APIs.

Responsibilities:

• Implemented key parts of sender registration system supporting multiple messaging channels (WhatsApp, RCS and potentially others), handling provider-specific requirements and compliance rules.
• Optimized message delivery latency and reliability while maintaining complex business rules across different OTT providers.
• Resolved critical customer escalations through deep technical investigation and edge case analysis.
• Worked on updating billing logic on a critical path, ensuring accurate and timely billing for customers.
• Contributed to cross-team Scala, Golang and Java projects.

March 2021-October 2021

Marketing Project

Customer: US technology company

Developed and optimized Apache Spark pipelines processing cross-service engagement data with strict privacy preservation requirements across multiple digital entertainment and subscription platforms.

Responsibilities:

• Engineered high-performance Spark jobs processing TB-scale user engagement data.
• Built privacy-preserving data aggregation pipelines enabling anonymous cross-service analytics.
• Optimized data processing pipelines reducing job completion times while ensuring data minimization principles.
• Documented dataset lineage and data flow for compliance and reproducibility.

May 2020-March 2021

Healthcare Project

Customer: US healthcare technology company

Played key role in modernizing healthcare data processing platform, enabling efficient transformation of diverse medical records into analytics-ready formats for business intelligence.

Responsibilities:

• Transformed legacy Python batch jobs into scalable Apache Spark workflows, migrating complex healthcare data processing logic.
• Designed and implemented production-grade ETL pipelines handling diverse healthcare data formats from multiple source systems.
• Optimized large-scale data reprocessing jobs reducing execution time while ensuring HIPAA compliance.
• Developed automated AWS S3 to Redshift data pipeline using PySpark and boto3, enabling real-time BI reporting.
• Contributed significant technical input to architecture decisions affecting multiple project initiatives.

Oct 2019-May 2020

Adtech Project

Customer: Israel adtech company

Developed real-time ad analytics platform processing high-volume impression data (670+ MPS) to enable automated bidding decisions and campaign optimization.

Responsibilities:

• Implemented Spark Structured Streaming jobs for real-time ad performance analysis
• Optimized data processing architecture reducing operational costs while maintaining system reliability
• Modernized legacy Python ETL pipelines to improve maintainability and processing efficiency

Feb 2018-Oct 2019

Communications Project

Customer: US SaaS company

Developed high-throughput streaming applications for SMS data processing, implementing complex rate calculation logic and generating business intelligence insights.

Responsibilities:

• Optimized messaging metadata enrichment pipeline during Kinesis-to-Kafka migration, achieving 830+ MPS through elimination of processing redundancies.
• Implemented comprehensive cross-stream validation to ensure data consistency between source systems during the transition.
• Built cost-effective internal services replacing external API dependencies, resulting in significant operational savings
• Led Scala knowledge-sharing initiatives including mentoring sessions and technical workshops

Jun 2017-Dec 2017

Digital Transformation Project

Customer: US energy company

Contributed to enterprise-wide data modernization initiative, migrating traditional database workloads to cloud-based big data processing platform.

Responsibilities:

• Replaced legacy Oracle and MySQL batch processes with scalable Apache Spark pipelines
• Built new data processing workflows using Spark SQL and Hive, eliminating dependency on legacy SQL jobs

Nov 2015-Jun 2017

IoT Monitoring Platform

Customers: European food and beverage companies

Developed real-time monitoring system processing data from IoT sensors across warehouse and retail locations, enabling predictive maintenance and inventory optimization.

Responsibilities:

• Implemented scalable data processing pipelines using Apache Spark and Akka Streams to handle real-time sensor data
• Built diagnostic tools enabling QA and hardware teams to validate device performance and data accuracy
• Developed anomaly detection system for early identification of hardware issues

Education

2016-2017 MSc Degree, Computer Science, Lviv Polytechnic National University, Ukraine

Professional Development

2023 Natural Language Processing & AI

• Contributed Ukrainian localization and dataset improvements to OpenAssistant/oasst1 open-source project
• Built practical applications using transformer models and HuggingFace libraries
• Explored large language models and their enterprise applications

2022 Deep Learning & Time Series Analysis

• Completed fast.ai’s Practical Deep Learning for Coders course
• Implemented time-series forecasting solutions using Facebook’s Prophet
• Applied deep learning techniques to real-world data problems

Languages

English - Advanced