Md Tamim

Lead Data Engineer with 11+ years of experience designing large-scale data platforms, ETL pipelines, and customer-centric data solutions on cloud-native architectures. Proven expertise in data modeling, real-time and batch processing, and building analytics-ready data warehouses for high-volume systems in the payments domain. GCP Certified Professional Cloud Architect with a strong track record of leading high-impact digital transformation projects in the payments industry.

Actively exploring GenAI-driven capabilities in data engineering, including intelligent data discovery, automated query generation, and data validation/testing workflows. Seeking a Data Architect role to architect scalable data platforms and empower business with data-driven decision-making.

Lead Data Engineer at Impetus Infotech India Pvt. Ltd (2018-11 – Present)

Client: American Express

• Designed and optimized data lake on GCP supporting high-volume ingestion, transformation, and query workloads.
• Designed customer-centric data models by integrating multiple source systems enabling identity resolution to generate unified 360-degree customer views for marketing.
• Enabled customer segmentation and personalization by delivering a unified customer dataset through MDM-driven data consolidation, supporting marketing use cases such as targeted offers and behavioral insights.
• Worked on star and snowflake schemas for enterprise data warehouse handling complex fact and dimensional data models utilizing SCD techniques to improve query performance along with historical data tracking
• Optimized warehouse schemas using partitioning, clustering and denormalization techniques to improve query performance and reduce processing costs by up to 90% in certain cases.
• Designed and led development of batch and realtime data pipelines using PySpark, BigQuery, Hive and Kafka.
• Led migration from legacy NiFi ETL pipelines to distributed Spark/Hive architecture, improving data processing throughput by 10x and reducing latency for business-critical datasets.
• Managed 15+ microservices on Kubernetes (GKE) using Helm charts, enabling auto-scaling, resilience, and achieving 99.99% system uptime.
• Integrated SonarQube into CI pipeline, achieving 80%+ JUnit test coverage and improving code quality with static analysis enforcement.
• Built and optimized CI/CD pipelines (Jenkins, GitHub Actions), automating testing, builds, deployments, and security checks—improving release frequency by 40%.
• Led code reviews to enforce design and security best practices, improving code maintainability and reducing bugs by 30% across teams.
• Drove tech debt reduction by modernizing dependencies and fixing CVEs, enhancing code security and long-term maintainability.
• Co-led large-scale cloud migration from on-prem to GCP, re-architecting systems for scalability and reducing infra costs by 25%.
• Established centralized observability solutions using Splunk, ELK Stack, and OpenTelemetry, creating realtime alerting and dashboards enhancing system reliability and proactive issue detection.

Associate Developer at Cognizant Technology Solutions (2017-02 – 2018-10)

Client: Mattel

• Developed high-reliability REST APIs using Spring Boot, optimizing query layer to improve response time by 30%.
• Reduced incident resolution time by 50% through proactive performance profiling and logging improvements.

Programmer Analyst at Cognizant Technology Solutions (2014-10 – 2017-01)

Client: Homebase

• Built and maintained enterprise backend modules (Java, Hibernate, DB2), optimizing legacy SQLs and reducing query latency by ~25%.
• Implemented unit and integration testing strategies, improving application reliability and ensuring seamless module interactions.

B.Tech in Electrical – B. P. Poddar Institute Of Management And Technology (2014-01 – 2014-01)

Class 12 – Kendriya Vidyalaya Barrackpore(Army) (2009-01 – 2009-01)

Class 10 – Kendriya Vidyalaya Barrackpore(Army) (2007-01 – 2007-01)