Arash Haydari

Data Engineering and Pipeline Design:
Data Processing and Integration: Leveraged Apache Spark and Databricks for efficient data ingestion and processing, ensuring robust data handling.
Data Modeling: Applied DBT and Data Vault methodologies to design and implement complex data models, structuring data in multi-layered architecture (Bronze, Silver, Gold).
ETL Process Development and Maintenance: Developed and maintained scalable ETL pipelines, integrating various data sources and ensuring smooth data flow.
CI/CD Deployment: Managed end-to-end CI/CD deployment processes using Jenkins, Terraform, and Bitbucket, streamlining integration and delivery cycles.
Testing and Quality Assurance: Created and implemented comprehensive test scenarios to verify data integrity and reliability across all stages.
Source and Destination Management: Integrated data from diverse systems and distributed it to various platforms and third-party services, optimizing data utilization for business growth and customer experience enhancement.
Collaboration and Workflow Automation:
Pipeline Automation: Partnered with data scientists and engineers to automate data workflows, enhancing efficiency and accuracy in data processing.
Continuous Improvement: Conducted performance tuning and optimization of data jobs, reducing latency and improving resource utilization.
Internal Training and Mentorship: Provided guidance and training to junior engineers on best practices in data engineering, focusing on the strategic use of Databricks, DBT, and other technologies.
Focus: Apache Spark, Databricks, DBT, Data Vault, Jenkins, Terraform, Bitbucket, CI/CD, Data Integration, Data Modeling, ETL
Designed and implemented data pipelines using Apache Spark and Databricks, ensuring efficient data ingestion and processing.
Modeled data using DBT and Data Vault methodologies, structuring data in multiple layers (Bronze, Silver, Gold) for optimal reporting and analysis.
Developed and maintained ETL processes to integrate and manage data from various sources, ensuring smooth data flow and storage.
Managed CI/CD deployment processes with Jenkins, Terraform, and Bitbucket, streamlining development and deployment cycles.
Created and executed comprehensive test scenarios to ensure data integrity and reliability across all processing stages.
Integrated data from diverse systems and distributed it to various platforms and third-party services, enhancing data utilization for business growth and improved customer experience.
Automated data workflows in collaboration with data scientists, improving efficiency and accuracy in data processing.
Conducted performance tuning on data jobs to reduce latency and improve resource utilization.
Mentored and trained junior engineers on best practices in data engineering, focusing on technologies such as Databricks, DBT, and CI/CD tools.
Technologies: Apache Spark, Databricks, DBT, Data Vault, Jenkins, Terraform, Bitbucket, CI/CD, Data Integration, Data Modeling, ETL

• Focus: AWS Ecosystem & Google BigQuery
• Spearheaded the design and implementation of an AWS S3-based data lake, centralizing data storage with robust governance policies
• Established and enforced data governance and quality frameworks
• Developed and maintained ETL processes using Airflow and AWS Glue, optimizing the data pipeline for scalability and maintainability
• Mentored junior engineers in best practices for cloud-based solutions, particularly AWS services
• Introduced data versioning for traceability and compliance
• Conducted performance tuning on SQL queries, reducing latency
• Collaborated with data scientists to automate machine learning workflows
• Played a key role in data migration projects, ensuring zero downtime
• Led internal training sessions to uplift data literacy within the organization
• Worked closely with business analysts to implement tailored BI solutions
• Technologies: AWS Glue, AWS Redshift, Google BigQuery, Airflow, S3, Python, SQL

• Focus: On-Premises & Cloud-based Data Solutions
• Engineered and managed high-availability database systems
• Automated routine database tasks, reducing manual effort
• Conducted code reviews and quality assurance tests
• Played an integral role in optimizing existing ETL processes
• Assisted in the modernization of the data stack, integrating cloud-based solutions
• Conducted PoCs for new technologies, presenting findings to executive leadership
• Guided the organization in best practices for database scaling
• Collaborated with cybersecurity teams to ensure data privacy and compliance
• Technologies: Python, SQL, Oracle, PostgreSQL, ETL Tools

• Orchestrated a large-scale data transformation project, improving data consistency
• Developed automated testing suites for data pipelines
• Managed data sync processes between disparate data sources, ensuring data consistency
• Fostered cross-departmental communication for a unified data strategy
• Created and deployed SQL-based analytics reports for business units
• Collaborated in the design and implementation of the company’s first data lake
• Implemented metadata tagging for better data discoverability
• Developed data quality checks that reduced errors
• Recommended architecture improvements, tool solutions, and acted as a technical advisor
• Technologies: SQL, Python, Hadoop, Hive, Spark

• Engineered and optimized stored procedures for data retrieval
• Automated monthly data aggregation tasks, improving efficiency
• Designed data models for reporting and analytics
• Played a key role in several data migration initiatives
• Acted as the primary contact for data-related queries from business units
• Advised on best practices for data visualization
• Created reusable Python scripts for data extraction tasks
• Collaborated with IT to ensure uptime and data security
• Technologies: Python, SQL, Bash

• Focus: Revenue Assurance and Fraud Management
• Developed code and procedures for repeatable data retrievals, summarized by desired groupings
• Served as a technical/data subject matter expert, reporting to multiple business units
• Conducted data analysis to provide actionable insights for executive-level management
• Managed large data sets and derived conclusions from complex analytics
• Worked on fraud detection algorithms, contributing to risk mitigation
• Introduced a modular approach to ETL development, significantly enhancing maintainability
• Technologies: SQL, Bash, Oracle