Anas Malik Email & Phone Number

San Francisco Bay Area

I lead and mentor a dynamic team of data engineers in the design, development, and optimization of robust and scalable data infrastructure. My expertise lies in understanding complex business requirements and translating them into actionable data-driven solutions.Key Responsibilities and Achievements:Strategic Leadership: Set the vision and strategy for the data engineering function, ensuring alignment with organizational goals and industry best practicesTeam Development: Recruit, mentor, and provide career growth opportunities for a team of data engineers, fostering a culture of continuous learning and innovationArchitecture & Design: Oversee the design and implementation of reliable data pipelines, ensuring data accuracy, scalability, and optimal performanceStakeholder Collaboration: Collaborate closely with data scientists, analysts, and business units to understand needs and ensure the delivery of meaningful data solutionsOptimization: Regularly review and optimize existing data processes and infrastructure, driving improvements in efficiency and reducing costsTechnology Stewardship: Stay abreast of the latest developments in data engineering technologies and tools, ensuring our stack remains cutting-edge and relevantSkills & Proficiencies:> Experience with big data tools (e.g Spark, Kafka)> Proficient in cloud platforms (GCP, Azure) and setting up data lakes and warehouses> Strong understanding of database architecture, ETL processes, and data modeling principles> Demonstrated ability to manage and prioritize multiple projects and tasks concurrently.> Excellent interpersonal and communication skills, bridging technical and non-technical audiences

Bangalore

Stepping into the world of cloud architecture, I have embraced the role of an Azure Junior Cloud Architect as well as a Data Engineer at PwC. My journey has been a blend of rigorous learning, hands-on development, and collaborating with senior architects to craft scalable cloud solutions tailored for our organization's needsKey Responsibilities & Achievements:Data Lakes & Warehousing: Designed and deployed an Azure Data Lake Store, integrating it seamlessly with Azure Data Factory to automate ETL processesSolution Design: Assisted in designing robust Azure-based cloud architectures, ensuring resilience, scalability, and optimal performance.Azure Resource Management: Deployed and managed a variety of Azure resources such as VMs, Azure Blob Storage, and Azure SQL Databases, enhancing the operational efficiency of Fedrigoni's cloud infrastructureInfrastructure as Code (IaC): Gained proficiency in using Azure Resource Manager templates and Azure DevOps for consistent and repeatable deploymentsSecurity & Compliance: Collaborated with the security team to ensure best practices are in place, implementing Azure policies and Blueprints for consistent governance across resources

Bangalore

As an SAP BODS ETL Engineer at EY, I harness the power of BusinessObjects Data Services to facilitate and optimize the integration, transformation, and improvement of enterprise data. My role is a blend of technical prowess, collaboration, and a commitment to ensuring data integrity and efficiency throughout our organization.Key Responsibilities & Achievements:ETL Design & Optimization: Led the design, development, and enhancement of complex ETL processes using SAP BODS, improving data load times by 50% and ensuring reporting data availability for critical business operations.Data Quality & Governance: Implemented data quality transformations in BODS, reduced data discrepancies and increasing trust in our analytical outputs.SAP Integration: Collaborated closely with SAP teams to ensure seamless integration between SAP BODS and other non SAP modules like Amazon Redshift and SybaseIQ, facilitating more accurate and efficient reporting.Troubleshooting & Support: Acted as the primary point of contact for troubleshooting ETL-related issues, maintaining a 100% success rate in resolving tickets within the stipulated SLAs.Continuous Improvement: Conducted periodic reviews of existing ETL processes, recommending and implementing improvements that boosted performance and reduced resource consumption.

Bengaluru Area, India

Amazon Redshift ETL Engineer (using SAP BODS) at Dun & BradstreetI blend the capabilities of Amazon Redshift's data warehousing solutions with the prowess of SAP BODS to drive sophisticated ETL processes. My expertise lies in harnessing these platforms to ensure timely, accurate, and efficient data integration, transformation, and loading in support of our business intelligence initiatives.Key Responsibilities & Achievements:Redshift ETL Development: Designed, developed, and optimized ETL processes for extracting data from various sources and loading into Amazon Redshift, achieving a 50% improvement in data processing speeds.SAP BODS Integration: Spearheaded the integration of SAP BODS with Amazon Redshift, allowing for more advanced transformations and a streamlined ETL process tailored for our BI needs.Data Quality Assurance: Leveraged SAP BODS's data quality functionalities to cleanse, deduplicate, and standardize data before loading into Redshift, ensuring that our analyses are based on clean and reliable data.Performance Tuning: Continually monitored and optimized query performance in Redshift, reducing query run times and ensuring rapid data retrieval for end-users.Collaboration & Training: Worked closely with data analysts, data scientists, and other stakeholders to align ETL processes with business goals. Also conducted training sessions, sharing expertise in Redshift and SAP BODS with the wider team.

Cochin Area, India

> Specialized in designing and deploying ETL processes with Informatica PowerCenter, ensuring robust data integration and migration.> Expert in data modeling, translating business needs into efficient database structures.> Championed Informatica Data Quality (IDQ) tools to guarantee clean, consistent data.> Mastered performance tuning, optimizing ETL jobs for maximum efficiency.> Integrated data from a mix of sources: relational & NoSQL databases, cloud platforms like AWS.> Managed seamless transitions across dev, test, and prod environments.> Collaborated with cross-functional teams, ensuring data readiness for analytics & reporting.> Continuously updated with the latest data engineering trends and Informatica advancements.