Максим

Maksym Muchak
Senior / Lead Data Engineer
Europe (Remote) | [открыть контакты](см. выше в блоке «контактная информация») | LinkedIn | GitHub
SUMMARY
• Data engineering lead who built Argus Media's analytics platform from the ground up — a Redshift + S3 lakehouse processing ~50 GB/day across
200+ tables, now used daily by 8 analysts and data scientists to support commodity pricing and market intelligence. I lead a cross-functional
team of 8 (3 DE, 2 QA, 2 DevOps, 1 BA) and own everything from CDC ingestion to governance and cost control.
• 5+ years shipping production data systems on AWS and Snowflake across energy, telecom, banking, and entertainment. I care most about the
boring-but-critical stuff: pipeline reliability, honest cost accounting, schema contracts that actually hold, and making analysts self-sufficient so
they stop filing tickets.
EXPERIENCE
Technical Lead (Data Engineering), Argus Media — Remote (UK / EU) Dec 2024 – Present
• Own the end-to-end data platform — CDC ingestion, dbt transformation layers, Redshift + S3 lakehouse, and Lake Formation governance.
Responsible for platform reliability, data freshness SLAs, and cost optimization across all production pipelines.
• Designed blue-green CDC routing with automated cutover validation to enable zero-downtime database migrations — a hard requirement after
an earlier full-resync incident cost 3 days of analyst downtime.
• Introduced schema validation contracts at ingestion time and DLQ-based error handling; reduced mean time to detect breaking upstream
changes from ~hours (analyst complaints) to ~minutes (automated alerts).
• Made the call to keep Redshift Spectrum over a full Iceberg migration after benchmarking showed our query patterns didn't justify the complexity
— saved the team ~2 months of migration work and avoided a premature architecture bet.
Senior Big Data Engineer, Argus Media — Remote (UK / EU) Feb 2024 – Dec 2024
• Built the initial dbt layer (staging → intermediate → marts) from scratch across 5 datalake S3 buckets; standardized naming, testing, and
documentation conventions that the team still uses.
• Saved ~$100K+/year by implementing S3 lifecycle policies, Intelligent Tiering, and automated cleanup of orphaned data — work that required
auditing years of accumulated storage nobody had touched.
• Shipped monitoring and alerting (CloudWatch + SNS) for critical pipelines; SLA breaches dropped, but honestly the real win was that on-call
engineers stopped guessing which pipeline was broken.
Data Engineer, IdeaSoft.io — Kyiv, Ukraine (Remote) Nov 2023 – Feb 2024
• Joined a high-traffic entertainment platform mid-flight with zero handover — previous team was gone. Deep-dived the existing
MSSQL-to-Snowflake migration in days, stabilized it, and co-owned ongoing operations with one other engineer while on-call for hourly batch
loads.
• Chose batch ingestion (Glue → S3 → Snowflake) over Kinesis/EMR after assessing latency requirements — real-time wasn't justified, saving
significant infrastructure complexity and cost.
• Guided 10 downstream data engineers in building a medallion architecture (bronze/silver/gold) in dbt on top of the migrated data, establishing
modeling standards for the wider team.
Data Engineer, AM-BITS LLC — Kyiv, Ukraine (Remote) Apr 2021 – Oct 2023
• Delivered data pipelines across telecom, banking, and government clients as part of a 5-person team (3 DE, 1 BA, 1 QA) in an outsourcing
consultancy.
• Telecom: Built real-time ingestion into Hive for a major telco. When the war started (Feb 2022), connector stability collapsed and data volumes
spiked unpredictably — ran on-call to scale nodes and threads, rewrote late-arrival handling on the fly. This data fed the systems that helped
engineers restore mobile coverage from damaged stations.
• Banking: Built Spark + Kafka pipelines that powered cashback assignment logic — calculating spend thresholds and dynamically adjusting reward
percentages in near real-time, directly supporting customer retention and card activation revenue.
• Migrated 17+ TB from Oracle to PostgreSQL, HBase, and Hive using Apache NiFi; reduced storage costs ~20% through optimized partitioning and
compression across Cloudera/HDP.
Data Engineer, MDM-Group — Kyiv, Ukraine Nov 2019 – Jan 2021
• Built Airflow-based ETL pipelines and partitioned Hive datasets on HDFS; reduced end-to-end data latency ~20% through query tuning and
pipeline parallelization.
SKILLS
Cloud: AWS (Redshift, S3, Glue, Athena, Lambda, Step Functions, Lake Formation, CloudWatch, CloudFormation), Snowflake
Data: dbt, Apache Spark, Apache Kafka, Apache NiFi, Apache Airflow / MWAA, Fivetran
Infrastructure: Terraform, CloudFormation, Docker, CI/CD (GitHub Actions)
Languages: Python, SQL
EDUCATION
National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Master in Insurance and Sep 2020 – May 2022
Financial Mathematics — Kyiv, Ukraine
National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Bachelor in Mathematics — Sep 2016 – Jun 2020
Kyiv, Ukraine
CERTIFICATIONS | LANGUAGES | VOLUNTEERING
Certifications: Cloudera Technical Professional (2022–2025), The London School of English — Advanced Level
Languages: English — Full Professional | Ukrainian — Native | Russian — Full Professional
Volunteering: IT Army of Ukraine — cybersecurity initiatives; Center for Pediatric Cardiology — blood donation programs