Pharm Sales Data Engineering Pipeline

@zyeloncomputech

Hi sir, Thank you for giving opportunity for biding... we have gone through your requirements and we can do your pharmaceutical Sales Data Engineering automation according to your exact requirements. Why You Need To Go With Us? And What Special you get with us. • Your vision = Our mission • Your idea + Our expertise = Winner on Web • Cutting edge web technology & design • Innovative, Cost effective & Customized service • Pragmatic Approach • Constant communication with clients • Consistent performance • On-time delivery • Maintenance of global quality standards • Your online business + Our experience = Your success Python, Data Analytics, Data Science Portfolio IoT Data Analysis for Dairy Refrigerator Temperature Monitoring Real-time Object Detection using OpenCV and YOLO Supply Chain Management System Enterprise Data Warehouse Implementation Cloud Data Lake Migration Web Application Development for Wind Turbine Performance Prediction Data Analytics Platform for Supply Chain Optimization AI Bill System AI Try Dress

@ParasTech7

Hello, I’m an IIT graduate with 21+ years of software engineering experience and currently working as a Principal Software Engineer at a major tech company. I have hands-on experience building large-scale AWS data engineering pipelines using Python, PySpark, Spark SQL, EMR, Lambda, Step Functions, S3 Data Lakes, CloudWatch, and SNS. I have worked on ETL workflows involving data ingestion, transformation, validation, data quality checks, orchestration, and delivery to downstream business systems. My experience includes building scalable data lake architectures, implementing business-rule-driven transformations, optimizing Spark workloads, automating pipeline monitoring, and supporting UAT and production deployments. I am comfortable working with large datasets, performance tuning, and ensuring reliable end-to-end data delivery. I would like to discuss. Please share more details.

@iterativeTech

As a seasoned data engineer with a strong inclination towards applied artificial intelligence, I've come across numerous projects where I've built and managed scalable ETL pipelines just like you require for your pharmaceutical sales data. My proficiency lies in using languages such as Python, SQL, and leveraging Amazon Web Services (including AWS Lambda) to set up dynamic, real-time architecture for efficient data processing. In addition, I have substantial experience with PySpark and Spark SQL - tools that are crucial for handling complex and voluminous datasets which characterize the pharmaceutical sales domain. Over the years, my work has spanned various industries like finance, health care, insurance among others; therefore I can assure you of not just technical expertise, but a deep understanding of the business side as well. Your project description emphasizes on accurate and timely decision-making which is where I can add significant value through my skills in implementing data quality checks aligned with BRD requirements.

@riteshkdev

Hi, I am a Software Engineer with hands-on experience in Python, SQL, ETL development, AWS, and data processing pipelines. My current work involves building and optimizing data workflows, implementing data quality checks, performing data transformations, and working with large datasets using Python and SQL. I have experience with: • Python and SQL development • ETL/ELT pipeline design and optimization • AWS services including S3, Lambda, CloudWatch, and data processing workflows • Data validation, cleansing, deduplication, and transformation • Pandas for data analysis and processing • Performance optimization and troubleshooting • Building scalable and maintainable data solutions The project aligns closely with my background in data engineering and cloud-based data processing. I can quickly understand business requirements, implement reliable data pipelines, and ensure high-quality data delivery. I am available to start immediately and would be happy to discuss the requirements in more detail. Regards, Ritesh Katwe

@arav38vilayatkar

Hello, Based on your requirements, I can help design and maintain a robust end-to-end pipeline that automates ingestion, validation, transformation, and delivery of pharmaceutical sales and CRM data. I have experience working with medallion architecture (Raw, Processed, Curated layers), large-scale Spark processing, data quality frameworks, and workflow orchestration in AWS environments. Key capabilities I can bring to this project: • Development of scalable ETL pipelines using Python, PySpark, and Spark SQL • AWS S3 Data Lake design with Raw, Processed, and Error zones • AWS Lambda-based file and schema validation • Step Functions orchestration and EMR job automation • Data cleansing, deduplication, enrichment, aggregation, and KPI generation • Region-specific business logic implementation, including data segregation workflows • Automated monitoring through CloudWatch dashboards, logs, and SNS notifications • Support for UAT, production deployment, and ongoing optimization • Experience handling high-volume datasets with performance tuning and cost optimization I understand the importance of data accuracy in pharmaceutical sales operations, territory alignment, HCP targeting, and CRM integrations. My focus is on delivering reliable, well-documented, and maintainable solutions that meet business requirements while ensuring data quality and operational stability. Best Regards.

@sgwtechnology

Designed and implemented end-to-end AWS data engineering pipelines using Python, PySpark, Spark SQL, and AWS EMR to process pharmaceutical sales, HCP, and territory data for Veeva CRM. Built medallion architecture on S3 (raw, processed, error zones) with automated ETL, EU/RU data bifurcation, and business rule validation. Developed Lambda triggers, Step Functions orchestration, and EMR jobs for scalable processing. Implemented data quality checks, KPI generation, and monitoring via CloudWatch and SNS alerts. Delivered curated datasets to Veeva CRM for sales insights and field operations.

@arpitsinghde90

This project mirrors work I've done in production. I've built medallion architecture ETL pipelines on AWS EMR using PySpark and Spark SQL, designed S3 data lake structures (raw/processed/error zones), orchestrated workflows via Step Functions, and implemented Lambda-based validation triggers - exactly the stack you've listed. I've handled multi-region data bifurcation with region-specific business logic, multi-layer data quality checks against BRD requirements, and CloudWatch + SNS monitoring setups. CRM data delivery pipelines with deduplication, aggregation, and KPI generation are well within my wheelhouse. AWS Certified Data Engineer. 13+ years in data engineering. Ready to hit the ground running.

@MartinusDanteB18

"We recently wrapped up a project very similar to this, helping a client build a data engineering pipeline for service businesses. We'll help you achieve streamlined data processing and delivery, integrating seamlessly with Veeva CRM. Your focus on clean, professional data handling aligns perfectly with our expertise in Python, SQL, ETL, PySpark, AWS EMR, and more. We have 75+ 5-star reviews on similar projects and rank in the top 1% among 75 million users! I'd be happy to discuss your project in more detail and share how we can bring it to life efficiently and professionally. Best case, we work together. Worst case, you get free advice that helps you move forward. Regards, Martinus."

@arpitshridhar

Recently, I worked on an AWS-based data engineering project that processed pharmaceutical sales, HCP, territory, and marketing data for Veeva CRM. Using Python, PySpark, Spark SQL, AWS EMR, Lambda, Step Functions, and Amazon S3, I built scalable ETL pipelines that automated data ingestion, validation, transformation, and delivery to downstream business systems. The pipeline included data quality checks, deduplication, KPI generation, region-specific business logic, and monitoring through CloudWatch and SNS alerts. This helped ensure reliable and timely data delivery for sales planning and reporting teams. Project details and sample architecture can be shared during discussion. Availability: 40 hours/week Time Zone: IST (UTC+5:30) English Proficiency: Professional working proficiency. I regularly document technical solutions, collaborate with team members, participate in requirement discussions, and provide project updates in English.

@PrudhviReddy16

I am an excellent fit for this opportunity because I combine deep cloud data engineering expertise with a proven track record of building and optimizing end-to-end, enterprise-scale pipelines. My hands-on experience includes designing automated, region-specific ETL workflows using Python, PySpark, and Spark SQL, as well as orchestrating complex, event-driven serverless architectures with AWS Step Functions, Lambda, and EMR. Furthermore, my background at American Airlines focuses heavily on cloud platform optimization, cost reduction, and strict data privacy compliance. This dual experience ensures that I do not just write functional code—I architect secure, scalable, and highly efficient cloud infrastructure that minimizes compute costs while delivering reliable data availability.

@mahekb28

Hello, I am a Data Engineer with expertise in Python, SQL, PySpark, Spark SQL, ETL development, and AWS cloud services including EMR, Lambda, Step Functions, S3, CloudWatch, and SNS. Recently, I designed and implemented an end-to-end AWS-based data engineering solution for a pharmaceutical organization. The project automated ingestion of sales, HCP, territory, marketing, and call activity data from external APIs, processed large datasets using PySpark on AWS EMR, and delivered curated outputs to Veeva CRM. Key contributions included: • Building scalable ETL pipelines using Python, PySpark, and Spark SQL • Designing S3 Data Lake architecture (Raw, Processed, and Error zones) • Implementing region-specific business logic and data bifurcation • Developing AWS Lambda-based validation and quality checks • Orchestrating workflows with AWS Step Functions and EMR • Performing data cleansing, deduplication, transformations, and KPI generation • Setting up monitoring and alerting using CloudWatch and SNS • Supporting UAT, production deployments, and stakeholder collaboration I focus on delivering reliable, scalable, and high-quality data solutions while ensuring performance optimization and business alignment. I would be happy to discuss your requirements and help build a robust data engineering solution tailored to your needs. Looking forward to working with you. Best Regards Mahek Baria

@shrinkhalar

Hi, I am a Senior Data Engineer with 9+ years of experience in Python, SQL, ETL, PySpark, Spark SQL, AWS EMR, AWS Lambda, Amazon S3, Databricks, Snowflake, and Airflow. I have designed and implemented scalable batch and real-time data pipelines, optimized Spark jobs, and developed reliable ETL workflows for large datasets. Based on your project description, I can build an end-to-end AWS-based data engineering pipeline with clean, maintainable code and proper documentation. I can start immediately, communicate regularly throughout the project, and focus on delivering a high-quality solution on time. I would be happy to discuss your requirements in more detail. Thank you for your time and consideration. Regards, Shrinkhala Rani