Pharma Data Lead/Architect
1 month ago
Data Lead/Architect – Strategy & Analytics, Life Sciences/Pharma
Summary
Data Lead/Architect will provide a combination of both technical and strategic capabilities to the team of Data engineers and analysts. Data Lead will bring deep experience in major commercial data sets i.e. Claims, Sales and Payer etc. Candidate should have background in bringing key insights through integration of variety of data sets to deliver data products, Data Lake and Datawarehouse solutions.
The successful candidate will have experience in the biopharma, Pharma consulting companies with a background in data strategy, Data integration, Data quality and a demonstrated track record of generating impactful insights that help enable successful project outcomes and inform commercial strategies and activities.
Responsibilities:
- Extensive experience in Data integration, Data warehouse, Datalake on cloud platforms such AWS
- Experience with pharma commercial data such IQVIA, SYMPHONY Sales, Claims, MMIT, Payer data etc.
- Lead the team of Data engineers and analysts in the development of Datawarehouse and data products
- Synthesize and communicate results to clients and internal teams through oral and written presentations;
- Create project deliverables and implement solutions;
- Advance problem-solving skills and build/elevate internal capabilities;
Qualifications:
- Bachelor's or master's degree required in any discipline with strong record of academic success in quantitative and analytic coursework such as finance, applied mathematics, management science, data science, statistics, econometrics or engineering;
- 8-15 years of relevant post-collegiate job experience
- Experience managing Data Engineering, Data strategy and Business Intelligence projects for US and Global Life sciences organizations.
- Deep experience in cloud technologies (AWS) and Business Intelligence tools (Tableau/Quicksight)
- Experience in ETL/ELT on AWS, native services in AWS for data quality and integration
- Experience working with Analytics teams
- High motivation, good work ethic, maturity and personal initiative;
- Strong oral and written communication skills;
- Close attention to detail, with a quality-focused mindset;
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