Data Engineer/ Data Analyst

Role & responsibilities

Data Engineer will support building data pipelines onto Data Lake combining several data sets to enable the team to perform univariate and multivariate analysis for Sales, claims and Payer data for Commercial, Sales Operations and Market Access teams.

He / she will be responsible to build data pipelines on AWS using native tools and technologies to synthesize key insights from analysis to provide strategic recommendations and implications, as appropriate.

Responsibilities include,

• Build and Enhance data ingestion pipelines - including performance Troubleshooting & Remediation of reported errors at different tiers
• Communication with external data providers in case of source data issues for resolution

Required Skills 

• Overall knowledge of AWS data stack and DevOps tools, Gitlab, Kubernetes
• Knowledge of ETL tools like AWS Glue, Talend, DBT, Python, SQL etc.
• Knowledge of SFDC, RedShift, AWS S3, AppFlow, SFTP, GitHub
• Sound knowledge of life sciences commercial data operations. 
• Deployment expertise on cloud platforms like AWS
• CI/CD, GitHub/GitLab, DevOps skills like Jenkins for pipelines

Preferred candidate profile

• Bachelor's or master's degree (Applied Mathematics, Management Science, Data Science, Statistics, Econometrics or Engineering)
• 2-5 years of relevant post-collegiate job experience
• Extensive experience in Data lake architecture, building data pipelines using AWSservices like EC2, Lambda, Redshift, Glue,Athena, EMR, Cloudwatch, S3.
• Must be proficient in Python and SQL
• Experience working on Pharma commercial syndicated data such as IQVIA, Symphony, Claims, Payer, CRM and MDM data
• High motivation, good work ethic, maturity and personal initiative;
• Strong oral and written communication skills;

Perks and benefits