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Mike LunML

Mike Lun

Cloud/Data Platform Engineer

€400/day
Berlin, DE
8-15 years

Average response time: 1 hour

About Mike

Cloud Architect | Cloud Engineer | Data Engineer | Data Platform Architect with 10+ years of experience building large-scale cloud and data platforms in AWS, GCP, and Azure. Proven track record designing data lakes and warehouses, optimizing pipelines processing billions of records, and improving reliability through strong data modeling, observability, and SRE practices. Experienced technical leader who bridges data engineering, platform, and analytics to deliver measurable business impact.
  • English

    Native or bilingual

Can work on-site
Berlin (up to 50km)

Experience

  • BrewLogix
    Director of Cloud Architecture
    June 2022 - June 2025 (3 years)
    • • Spearheaded AWS cloud architecture strategy for five applications (~2,500 users). Implemented data platform cost optimizations across storage, compute, and query patterns, reducing overall AWS spend by ~60% while improving performance.
    • • Designed and implemented a tiered data lake using PySpark and AWS Glue for workflow orchestration, schema management, and schema evolution. Raw, CDC data, is ingested via Kinesis then formatted for consistency and flattened in tier one. Then the data is normalized and stored in Apache Iceberg format for tier two. In tier 3, the data is merged and optimized for analytics and stored in parquet tables.
    • • Built and led a team of 5 cloud engineers and data architects, responsible for IaC, data pipelines, API development, CI/CD, authorization, and monitoring, ensuring adherence to best practices through AWS Well-Architected Reviews.
    • • Built and maintained production-grade data pipelines powering analytics and ML use cases, including demand forecasting models that reduced customer inventory levels by 36%.Built ML models to predict product performance
    based on trends, events, style, and season, enhancing predictive analytics capabilities.
    • • Built and maintained production-grade data pipelines powering analytics and ML use cases, including demand forecasting models that reduced customer inventory levels by 36%.
    • • Established platform observability, monitoring, and CI/CD for data pipelines and infrastructure using CloudFormation, GitHub Actions, CodePipeline, Datadog, and CloudWatch.
    • • Architect for all Cloud and backend system design that included data pipelines, platform infrastructure (IaC), GraphQL API, Lambda Functions, IoT Core and led a team of engineers responsible for maintaining the code base.
    Amazon Web Services Apache Spark Python Infra as Code Amazon DynamoDB
  • Global Payments Inc.
    Lead IT Architect (Consultant)
    September 2021 - August 2024 (2 years and 11 months)
    • • Led migration from BigQuery to Snowflake, enabling cloud-agnostic architecture and data sharing, eliminating manual approval workflows that previously took up to 4 weeks.
    • • Designed schema for and built proprietary library for DAG/Airflow monitoring and alerting using Google Pub/Sub that protected customers from up to $1 M/ month in transaction fees.
    • • Architected SRE-focused observability using tools like Datadog and Google Cloud Observability to ensure data freshness, availability, and pipeline reliability.
    • • Defined SLIs and SLOs, optimizing system performance and security to support internal and external stakeholders across the organization.
    • • Partnered with data engineering and analytics teams to improve system scalability and operational resilience.
    SRE Principles Data Engineer SQL Snowflake Apache Kafka
  • TSYS
    Cloud Data Architect
    April 2021 - August 2021 (4 months)
    • • Built and maintained high-throughput batch and streaming data pipelines processing billions of daily payment transactions.
    • • Optimized BigQuery schemas for analytics using caching and Materialized Views, managed Airflow workflows, and refactored DAGs; reducing runtimes by ~30% and cutting job dependencies by 62%.
    • • Led the architecture design process for Data Engineering and ETL teams, ensuring projects met strict security standards of payment processing.
    ETL (Extract, Transform, Load) Processes SQL Data Engineer BigQuery Python

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Education

  • Hands-On Essentials: Data Warehousing Workshop Hands-On Essentials: Collaboration, Marketplace & Cost Estimation Workshop Certfied Cicerone ®
    Hands-On Essentials: Data Warehousing Workshop Hands-On Essentials: Collaboration, Marketplace & Cost Estimation Workshop Certfied Cicerone ®
  • Bachelor of Science (BS)
    Iowa State University
    2007
    Bachelor of Science (BS)

Skill set

Categories