Muhammad A.

Most data pipelines break quietly. A job runs, nothing errors, and three weeks later someone notices the numbers are wrong, by then the damage is already in the reports. I’m Muhammad Akhtar, a Data and DevOps Engineer with 9 years across AWS, Azure, Kubernetes, and Python. I don’t just fix pipelines, I build data ecosystems that are reliable, observable, and maintainable without constant intervention. 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 - 𝗠𝗮𝗸𝗶𝗻𝗴 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗔𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗪𝗼𝗿𝗸: With no real infrastructure, there are no real pipelines. I design and optimize: ETL/ELT pipelines (Airflow, Dagster, dbt, Spark, Databricks) PostgreSQL, MySQL, MSSQL, Snowflake, Redshift, BigQuery Python-based automation and orchestration TimescaleDB for time-series workloads at scale Recent example: built a security data platform processing 200,000+ CVEs with sub-10ms query latency, minute-level anomaly detection on TimescaleDB continuous aggregates, and a live asset-to-vulnerability matching pipeline, zero full-table scans at scale. 𝗖𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀 - 𝗧𝗵𝗲 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗕𝗲𝗵𝗶𝗻𝗱 𝘁𝗵𝗲 𝗗𝗮𝘁𝗮: Pipelines are only as reliable as what runs underneath them. I build and manage: AWS (EC2, RDS, Glue, S3, Lambda, Redshift, Step Functions) Azure (ADF, Azure DevOps, Cosmos DB, Monitor) Kubernetes (EKS/AKS), Docker, Helm, Terraform CI/CD pipelines - GitHub Actions, GitLab, Azure DevOps 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴, 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 & 𝗥𝗲𝗹𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Prometheus, Grafana, Datadog, CloudWatch, ELK IAM, RBAC, KMS, Cloudflare WAF, Aqua Security scanning SOC2, HIPAA, GDPR compliance readiness I act fast, communicate clearly, and treat your data infrastructure as something worth building properly the first time. Message me, I respond within an hour.