Associate Director, Data Engineering (BioPharm Communications LLC, New Hope, PA)

Perform Data Extraction and Integration with structured and unstructured data. Perform data preparation, transformation and extraction from various sources, including Snowflake, Oracle, SQL Server, Amazon S3, Azure, Google Ads, LinkedIn, Facebook. Develop automation jobs using Snowflake Task Scheduling to ingest data from diverse healthcare data sources like and others domain data points. Adopt cloud-based data integration service like Azure Data Factory and AWS Data Pipeline to create, schedule, and manage data pipelines that can move and integrate data from various cloud platforms into Snowflake. Perform Data Warehouse Management using central Snowflake Cloud Data Warehouse infrastructure, ensuring its continuous development and maintenance. Focus on building a robust foundation for efficient data storage, retrieval, and analysis within the Snowflake environment to support organizational data needs effectively. Work with NoSQL databases like MongoDB to analyze large volumes of semi-structured data for reporting and analytics. Overlook the building and maintenance of Salesforce Business Units for the marketing teams to execute campaigns, build automations and draw analytical insights to meet their reporting needs. Build database-centric web applications quickly and efficiently using low-code development platform like Streamlit, Oracle Apex etc. to create forms, reports and dashboards that interact seamlessly with the Oracle and Snowflake Database. Utilize various Python packages such as Numpy, Pandas, Matplotlib, and Scikit-learn for statistical calculations, data analysis, and drawing conclusions from extensive datasets. Build and create interactive dashboards and applications to allow interaction with underlying data in Snowflake. Utilize Databricks to run complex queries and work with large volume of streaming structured and unstructured data. Perform complex Excel operations, including v-lookups and Pivot Tables, for data analysis. Utilize visualization tools such as Tableau and Excel to analyze pharmaceutical data trends. Utilize Google Analytics and automated report generation using APIs. Utilize GitHub/Bitbucket for version control and code sharing within the team. Implement Machine Learning solutions with two, or more, cloud frameworks (e.g., AWS Sagemaker, Azure ML Studio, Google Cloud Vertex AI). Implement machine learning models in production. Develop models and other data science work utilizing Python. Position allows telecommuting from anywhere in the U.S. Salary Range: $136,011 – $146,000 per year.

MINIMUM REQUIREMENTS: Master’s Degree or U.S. equivalent in Applied Computer Science, Informatics, Information Systems, or related field, plus 3 years of professional experience as a Business Analyst, Data Engineer, or related occupation/position/job title involving Data Extraction and Integration.

Must also have experience in the following: 3 years of professional experience utilizing Programming Languages including SQL, Python, Scala, and Spark; 3 years of professional experience utilizing Web Technologies including HTML5, CSS3, JavaScript, or Bootstrap; 3 years of professional experience utilizing Packages including Numpy, Pandas, Matplotlib, and Scikit-learn and utilities including MATLAB, Jupyter Notebook, Visual Studio Code, X-Code, Lucid Chart, or Postman; 3 years of professional experience utilizing Databases including Snowflake, MySQL, Oracle12c, MS-Access, or MongoDB; 3 years of professional experience utilizing Data Visualization Tools including Tableau, Microsoft Excel, or Google Analytics and Version Control including GitHub; 3 years of professional experience utilizing Data Integration Tools including Databricks, Talend, Azure Data Factory, and FiveTran; 3 years of professional experience working with Operating Systems including Windows, MacOS, or Linux; and 3 years of professional experience utilizing Team Collaboration Tools including Slack and Teams.