Mehedi H.

Passionate, and detail-oriented Analytics Engineer with a strong focus on bridging the gap between data engineering and business analytics to empower self-service analytics and drive informed decision-making. Committed to continuous improvement though experiences and always eager to take on new challenges that make a real impact. Self Initiated Projects ✅ Core Banking Data Mart Automation - dbt | Airflow | PostgreSQL 🔗 ▶ Designed and implemented an end-to-end ATM Withdrawal Transaction Data Mart using dbt (Bronze–Silver–Gold layers) on PostgreSQL, incorporating incremental models, data quality tests, and freshness checks. ▶ Orchestrated automated 10-minute incremental updates using Apache Airflow, enabling nearly real-time data availability for downstream analytics. ✅ Core Banking System – ATM Withdrawal Streaming Simulation - Databricks | PySpark | Delta Lake | Streaming ETL ▶Designed and implemented a core banking data model, including 6 reference tables, 5 entity tables, and a double-entry financial journal table to simulate ATM cash withdrawal operations. ▶Developed a high-volume synthetic data generator and real-time PySpark Structured Streaming pipeline in Databricks to simulate and transform 100,000+ double-entry ATM transactions per minute into a unified Silver-layer data mart using Delta Lake, stream-stream joins, watermarks, and broadcast joins. ✅Real-Time Change Data Capture (CDC) Pipeline with Kafka, Debezium, and ClickHouse ▶Built a real-time data pipeline by setting up Kafka with Confluent Control Center and developing a Python Faker script to generate and stream 10M synthetic financial records. ▶Simulated a production system by sinking data into PostgreSQL, then enabled CDC with Debezium, replicating changes in real time to a ClickHouse target database with a custom-designed schema. ✅ Data Transformation with DBT ▶Built staging schemas and incremental models with well-defined schema documentation to enable efficient, modular data transformation, and ensure maintainability. ▶Developed custom macros to standardize logic and reduce code duplication and snapshots to manage slow-changing dimensions ✅ Technical Expertise: ▶ Languages & Platforms: Python, SQL; Microsoft Azure, Visual Code Studio, Jupyter Notebook, DBreaver, Docker ▶ Databases and Tools: Oracle, Postgre SQL, MySQL, ClickHouse ▶ Big Data Technologies: Apache Kafka, Airbyte, PySpark, dbt, Apache Airflow, Databricks ▶ Data Visualization: Tableau, Power BI, Metabase, Superset ▶ Microsoft: Advance Excel ▶ Soft Skills: Stakeholder Management, Time Management, Work Prioritization, Leadership ✅ Areas of Expertise : ▶ Data Architecture & Pipeline Engineering Proficient in designing and implementing real-time data pipelines, including CDC- enabled architectures, with a strong focus on scalable ETL/ELT processes and robust data modeling within modern data warehouse frameworks such as Medallion Architecture ▶Advanced SQL & Data Transformation Complex transformation logic using SQL, dbt, and custom macros to standardize logic across models ▶ Dashboard & Report Automation Create interactive dashboards in Tableau, Metabase, and Power BI supporting business units from sales to operations. ▶ FinTech Transaction analysis Customer analysis - Customer Lifetime Management, Campaign Analysis, Customer Cohort Development, Churn & Retention Analysis ▶ Inventory & Supply Chain Analytics Demand planning, Replenishment Model, Out of Stock analysis & Lost Sales, Safety Stock, Inventory Aging, Turnover, Product segmentation Industries I have worked for: FMCG, E-Commerce, FinTech(Mobile Financial Service)