Samuel Dallal Email & Phone Number

Lexington, Massachusetts, United States

In a leading pharmaceutical company, I worked as a Data Engineer within the Artificial Intelligence and Analytics (AIA) department of the development branch. The AIA department is tasked with designing and implementing AI solutions, initially using secondary data, and later integrating these models into clinical trials once proven. Our goal is to create production-level, modern, cloud-based pipelines that are validated and GxP compliant, often pioneering first-in-class solutions with the collaboration of the FDA and international regulators.Key Responsibilities:• Data Management: Managed both structured (SDTM) and unstructured data (doctor's notes), performing transformations, filtering, imputations, and aggregations to prepare data for model ingestion.• Refactoring and Modernizing Efforts of Structured Data Pipeline: Transitioned the data processing pipeline to a Glue/Lambda/Step Functions job combo with a CI/CD pipeline, storing code and Terraform Infrastructure as Code in Azure DevOps, then to a Databricks Integration. ETL scripting involved Python, PySpark, and SQL languages. • Creation of Unstructured Data Pipeline: Key collaborator in creation of OCR/Textract pipeline, initially in AWS and later transitioned to Azure. Specific responsibilities include leading development of Terraform and CI/CD pipelines, pre-processing code design, and collaboration on processing/post-processing of unstructured data.• Validation and Quality Assurance: Created numerous validation scripts and functions to ensure data integrity and accuracy, prior to, during, and after processing. contributing to the successful completion of product POC.• Digitization Project: Developed a functional pipeline using AWS Textract for OCR, later transitioning to Azure. Created a comprehensive instruction manual on building a Terraform pipeline.• Documentation

As a Data Engineer at a PBM and healthcare navigation startup, I played a vital role in designing and maintaining efficient data pipelines using AWS services. Working within a team, I developed and managed over 200 lambdas and dozens of Glue jobs, continuously optimizing code and collaborating with DevOps to provide quality technical solutions. My role also involved monitoring and resolving lambda failures and actively updating the CloudFormation code using Git for version control. Throughout, I embraced agile practices to ensure seamless project execution.• Designed, implemented, and maintained data pipelines using AWS services, including AWS Lambdas, Glue jobs, SQS queues, and RedShift tables• Optimized code and introduced function-based scripting methods to enhance the efficiency and scalability of data processing operations.• Authored comprehensive documentation outlining the procedures for updating the primary fact table supporting millions of medical claims processed daily.• Developed SQL code to facilitate ETL transformations and ensure accurate data integration across various systems and databases.• Monitored lambda failures, promptly identified and resolved issues, and collaborated with DevOps to ensure smooth and uninterrupted data processing.• Actively contributed to updating the CloudFormation code, playing a vital role in maintaining and enhancing the infrastructure's stability and scalability.

Greater Boston Area

Support the migration of a nation-wide home insurance company’s transition from on-prem servers to cloud data storage; from SQL Server to AWS to GCP, developing and creating ETL and data extraction solutions within SSMS, SSIS, SSRS, AWS CloudWatch, AWS Lambda, AWS Glue, AWS Athena, AWS S3, Splunk, Airflow, GCS, BigQuery, Terraform, GitLab, and more. Skills utilized include Python, TSQL, Pandas, and Apache Parquet.• Reduced runtime of process converting ~200,000 daily historic records of machine-readable, raw inspection data to human-readable, database-stored data by over 95%, from 24+ hours to under 1 hour. • Design, apply, and maintain SQL, Python, and PySpark solutions and scripts to ingest, clean, transform, connect, store and expose data for dozens of users across departments including program development, finance, and claims.• Member of a team focused developing an enterprise data warehouse (EDW), aggregating databases and centralizing information from five subsidiary companies in Google Cloud Platform, making property data available for use and analytics across the organization.• Apply new data sources by building pipelines for automated and semi-automated data ingestion and refresh serving property claims and enterprise finance teams.• Develop and maintain methods to match external and internal data through communication with stakeholders, database querying, analysis of raw files, and scripting adjusting for differences.• Design and implement tests to ensure data quality and proper governance across all integrated datasets in addition to and accordance to those of the enterprise governance and security standards.

Greater Boston Area

At General Assembly, I worked full-time on projects analyzing diverse datasets that utilized skills in Python, Pandas, Scikit-Learn, NumPy, Pandas, SQL, data munging, and webscraping, with an emphasis on delivering results and communicating finding.

Devens, Massachusetts

• Verified the accuracy of data aggregated by Aegis Discoverant during a transition from a local to global instance and helping coordinate solutions where errors arise, removing a barrier to cross-site method harmonization. • Navigate lab systems (LES, LIMS, Discoverant, TrackWise) to expedite data analysis and integrity.• Perform analysis of and compiled laboratory data for quarterly trending of quality with statistical software. • Communicated cross functionality with relevant stakeholders (QC Operations, SMEs, Quality) to investigate and address statistical trend alerts and root causes in the QC space.

Andover, Ma

• Aided a large pharmaceutical manufacturer and developer determine quality of product through a variety of cGMP verified methods including HPLC, robotic measurements of protein activity, concentration, and alkalinity, applying resultant values to algorithms that determined the continued validity of the manufacture and testing process.• Precisely performed quality control testing of multiple drug products, both finished and in-process, using a variety of lab techniques and processes in a BL-2 laboratory environment.• Successfully navigated a LIMS digital notebook system used to expedite data entry and integrity.• Performed data entry and data analysis using proprietary statistical software (JMP)

Master Of Science - Ms, Cloud Computing Architecture

Bachelor Of Science - Bs, Chemistry

ACS Certified Degree

Data Science

At General Assembly, I worked full-time on projects analyzing diverse datasets that utilized skills in Python, Pandas, Scikit-Learn.