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Muhammad Moiz AhmedMM

Muhammad Moiz Ahmed

Supermalter

Data Engineer, AWS, Data Vault 2.0, IaC, PySpark

€700/day
12 projects
Berlin, DE
15+ years

Average response time: 1 hour

Freelancer profile translated to English.
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About Muhammad Moiz

AWS & Multi-Cloud Data Platform Expert with Proven Track Record

I specialize in AWS architectures, cloud migrations, and data platform modernization with 15+ years of experience in enterprise projects. Experienced in Enterprise Architecture Advisory, Technical Reviews, and Team Mentoring.

Current Focus Areas:
  • AWS Services: Lambda, Glue Streaming (Kafka Consumers), Glue ETL, API Gateway, Aurora RDS, S3, DMS, Athena, Event Bridge
  • AWS Databricks, Azure Databricks, PySpark
  • Power BI Table Performance Optimization & MicroStrategy 10/11
  • Redshift RA3 (Distribution Keys, Sort Strategies, WLM Queues)
  • Unity Catalog, Delta Lake, Workflow Orchestration
  • Infrastructure as Code (Terraform/Terraspace, Liquibase)
Proven Track Record:
  • Appian: Enterprise Data Platform with AWS Glue & Lambda, Apache TIKA Integration
  • Circle K: 6M+ Daily Transactions, AWS Cost Reduction, 600+ Locations
  • Couche-Tard: Power BI + Redshift Performance Boost, 3-5x Photon Acceleration
  • TotalEnergies: AWS Transfer Family, SAP BOXI SFTP (Fingerprint) Integration, Process Automation
AWS Expertise:
  • Compute: Lambda, ECS (Docker Container), EC2
  • Data: Glue, Redshift, Aurora RDS, DMS, PostgreSQL, Athena
  • Storage: S3 (Lifecycle Policies, Cross-Account Access)
  • Integration: API Gateway, Transfer Family, EventBridge, GitHub OIDC
  • Security: IAM, KMS, OIDC, SCIM Passthrough
Data Engineering & Governance:
  • Python Development: Lambda, PySpark (Databricks), Glue Jobs, Shell/SFTP Scripting (SQL, Apache TIKA)
  • Data Processing: ELWIS, PEGELONLINE WSV, DWD Datasets
  • Compliance: GDPR Implementation, Data Classification Strategies
  • Documentation: Comprehensive Standards, API Design Patterns
  • Performance: Distribution Keys, Sort Strategies, WLM Queue Optimization
Additional Core Competencies:
  • Database Expertise: Aurora RDS Postgre, Oracle (OCP 11g DBA certified), Redshift, Exasol
  • Data Modeling, DV2.0, 3NF, Canonical
  • German

    Conversational

  • English

    Native or bilingual

  • German

    Fluent

  • English

    Fluent

Remote only
Primarily works remotely

Experience

  • Transport - Public Sektor
    Lead Data Engineer - Appian Data Platform
    TRANSPORTATION
    November 2024 - Today (1 year and 7 months)
    Frankfurt am Main, Germany
    Leading enterprise data platform design and implementation with scalable architecture patterns and compliance-driven development.

    Enterprise Architecture & Solution Design
    • Designed Medallion Architecture (Bronze/Silver/Gold) supporting multiple data domains
    • Implemented serverless ETL pipelines using AWS Glue and Lambda with PySpark DataFrames
    • Created architectural blueprints for event-driven data ingestion using API Gateway and Lambda
    • Built Terraform modules following modular design patterns for reusable infrastructure
    Real-Time Kafka Streaming Pipeline
    • Architected enterprise Kafka-to-PostgreSQL streaming ETL processing 10,000+ messages/hour
    • Engineered AWS Glue Streaming job with advanced Kafka consumer group management
    • Built production monitoring: CloudWatch metrics, S3-based DLQ, correlation IDs
    • Implemented dual-layer database resilience: psycopg2 + RDS Proxy achieving 95%+ success rates
    • Designed micro-batch architecture with configurable windows
    Public Transport Infrastructure - Real-Time Search
    • Architected OpenSearch CDC ingestion processing 10,000+ records/minute
    • Implemented production Lambda function (Python 3.13, 3GB) with 1,000 events/batch
    • Resolved security compliance issues (tfsec, tflint, Bandit, Semgrep)
    • Achieved zero-downtime deployment using versioned OpenSearch Pipeline v2
    Infrastructure Patterns & Best Practices
    • Standardized Terraform module structure across 15+ modules
    • Implemented GitOps workflow with automated security scanning
    • Applied patterns: conditional resources, lifecycle controls, security group reuse
    • Established CloudWatch monitoring for pipeline health metrics
    Outcome:Enabled scalable platform supporting multiple domains with real-time streaming, search functionality, and standardized patterns ensuring compliance and operational excellence

    Technologies:AWS (Lambda, Glue, S3, API Gateway, Aurora Postgre, OpenSearch, RDS Proxy), Kafka, PySpark, Terraform, psycopg2
    Terraform AWS S3 AWS Lambda OpenSearch API Gateway
  • Circle K
    Project Data Manager / Data Engineer
    ENERGY AND UTILITIES
    April 2025 - July 2025 (4 months)
    Berlin, Germany
    Architected and executed AWS-to-multicloud migration for Circle K's data platform (AWS/Azure Databricks), designing cross-cloud data transfer solutions that modernized infrastructure while maintaining zero-downtime operations for 600+ retail locations.

    Cross-Cloud Migration Architecture:
    • S3-to-Azure Blob pipeline via AWS Databricks for cross-cloud data transfer from legacy AWS to Circle K Azure
    • Phased migration strategy maintaining single legacy AWS account for synchronization while transitioning workloads to Circle K environments
    • Unity Catalog volumes collaboration with Circle K metastore admins, defining schema structures and access patterns
    • Migrated from low-level Spark RDDs to high-level DataFrame APIs, enabling Photon acceleration for performance gains

    Infrastructure as Code & Automation:
    • Implemented Terraspace/Terraform Redshift stack and modules, with RA3 node configuration
    • Implemented Redshift native schedules with associated IAM roles for automated ETL workflows
    • Managed database scripts for database and schema definitions / user access management

    Data Pipeline Modernization:
    • Refactored multiple Python notebooks from AWS Databricks to Azure Databricks, optimizing for Photon accelerator
    • Implemented Unity Catalog Delta tables for daily POS data processing with automatic schema evolution
    • Created weekly KPI / reports using Databricks views analyzing product volumes and sales metrics
    • Migrated data pipelines from sequential processing to parallel Spark operations

    Outcome:orchestrated zero-downtime migration serving 6M+ daily transactions; scalable cross-cloud architecture supporting both AWS and Azure workloads, reduced operational costs by 40% through infrastructure consolidation.

    Technologies: Azure Databricks, AWS Databricks, Terraform, Unity Catalog, Delta Lake, Redshift (RA3), S3 Cross-Account Access, IAM AssumeRole, Photon Engine, PySpark, Azure Blob Storage
    Databricks AWS S3 Python PySpark
  • Couche-Tard Deutschland GmbH & Co. KG
    Project Data Manager
    ENERGY AND UTILITIES
    November 2023 - March 2025 (1 year and 5 months)
    Berlin, Germany
    Managed cloud data infrastructure, focusing on Redshift optimization, Unity Catalog implementation, and AWS Databricks. Led performance tuning initiatives reducing query execution times across Power BI workloads.

    Redshift Performance Engineering:
    • Implemented distribution keys, sort/interleaved keys based on query pattern analysis
    • Established Workload Management (WLM) queues with memory allocation optimization for concurrent Power BI refresh jobs and Pipeline workloads
    • Configured RA3 node clusters with managed storage enabling independent compute/storage scaling
    • Created monitoring views for table statistics, query performance, and skewness tracking
    • Advised VACUUM strategies during pipeline runs, optimizing table performance
    • Implemented automatic snapshot schedules for recovery scenarios

    Databricks Platform Establishment:
    • Secured AWS Databricks access from parent organization through governance approval process
    • Implemented Terraform modules for Unity Catalog setup with three-level namespace (catalog.schema.table)
    • POCs for AWS Databricks adoption over Redshift, for performance and cost improvements, using Delta tables
    • Built data pipelines for public and internal data sources, using Spark RDD parallel processing
    • Built data quality monitoring completeness KPIs

    AWS Infrastructure Management:
    • Managed subnet groups and CIDR block allocations for Redshift cluster isolation
    • Configured cluster resize operations from dc2.large to RA3.xlplus nodes with minimal downtime
    • Managed Power BI Gateway Data Sources, and Network Firewall Whitelisting b/w OnPrem and Cloud using FQDNs

    BOXI to Cloud Data Integration:
    • Integrated SAP BOXI SFTP Exports with AWS Cloud, using AWS Transfer Family and Fingerprint calculation approach

    Stack:AWS Redshift (RA3), Databricks, Unity Catalog, Terraform, WLM, Distribution Keys, Interleaved Sort Keys, Power BI, S3, Spark RDD, Python, Delta Lake
    Databricks AWS S3

Reviews

5.0

Out of 2 ratings

R

Reyhan

Couche-Tard Deutschland GmbH & Co. KG

Reviewed on 10/10/2024

Data Management: Mohammad MOIZ AHMED has demonstrated outstanding skills in the area of data management. He has efficiently organised and updated our data management systems, resulting in a significant improvement in data integrity and accessibility. His structured and methodical approach has enabled us to optimise data management and accelerate processes. Cloud Administration (AWS): Mohammad MOIZ AHMED demonstrated a strong understanding and technical expertise in cloud administration. He implemented effective strategies to secure and manage our cloud infrastructure. As a result of his efforts, system downtime was minimised and overall operational efficiency increased. Communication and Teamwork: Mohammad MOIZ AHMED has proven to be an excellent communicator, working effectively with internal teams and external partners. His ability to communicate complex technical information clearly and concisely has greatly improved knowledge sharing and collaboration within the team. Problem Solving: Mohammad MOIZ AHMED demonstrated exceptional problem-solving skills. He proactively identified potential pain points and developed innovative solutions to address them. His analytical thinking and proactive approach helped to overcome technical challenges quickly and efficiently.
R

Reyhan

Couche-Tard Deutschland GmbH & Co. KG

Reviewed on 10/10/2024

Data Management: Mohammad MOIZ AHMED has demonstrated outstanding skills in the area of data management. He has efficiently organised and updated our data management systems, resulting in a significant improvement in data integrity and accessibility. His structured and methodical approach has enabled us to optimise data management and accelerate processes. Cloud Administration (AWS): Mohammad MOIZ AHMED demonstrated a strong understanding and technical expertise in cloud administration. He implemented effective strategies to secure and manage our cloud infrastructure. As a result of his efforts, system downtime was minimised and overall operational efficiency increased. Communication and Teamwork: Mohammad MOIZ AHMED has proven to be an excellent communicator, working effectively with internal teams and external partners. His ability to communicate complex technical information clearly and concisely has greatly improved knowledge sharing and collaboration within the team. Problem Solving: Mohammad MOIZ AHMED demonstrated exceptional problem-solving skills. He proactively identified potential pain points and developed innovative solutions to address them. His analytical thinking and proactive approach helped to overcome technical challenges quickly and efficiently.

Recommendations

SB
Oleksandr ErmOE
Sefana Boucherit and 1 other person have recommended Muhammad Moiz

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