Data Engineer- Python, Pyspark, AWS, ETL

Key Responsibilities:
Develop and implement data governance policies and procedures to ensure data quality,
accuracy, consistency, and compliance with relevant regulations.
Design, develop, and optimize data pipelines for ETL processes using cloud services like
AWS, ensuring data security and access controls.
Collaborate with various stakeholders, including data scientists, analysts, and business
units, to understand data requirements and drive decisions.
Monitor data quality metrics, conduct regular data audits, and address data issues promptly
to maintain data integrity.
Provide technical leadership and consultancy to ensure cloud solutions align with
Enterprise IT architecture, and review system designs for cost-effective solutions.
Implement and manage data integration and migration projects, ensuring seamless data
flow across systems and maintaining comprehensive data catalogs.
Stay current with emerging data engineering technologies and best practices, and
document data engineering processes and standards.
Develop deep expertise in cloud platforms and technologies, assist with life cycle
management, and ensure coding standards are followed by External Service Providers.
Help establish a DevOps culture to improve the quality, security, and stability of cloud
solutions, and identify synergies for efficiency and cost savings.
Ensure compliance with data privacy regulations (eg: GDPR/ CCPA), manage data access
and permissions, and oversee the lifecycle of data from creation to archiving. Qualifications:
Proven experience as a Data Steward, Data Manager, or Data Engineer, preferably in a
cloud environment.
Strong business analysis skills and experience within pharma sales/commercial operations.
Ability to use analytics to drive meaningful insights.
Strong experience with Agile Development, CI/CD, Jenkins, GitHub, Automation platforms.
Strong analytical and problem-solving abilities.
Technical Experience:
Must Have: SQL, Python/PySpark, AWS Data Services such as Glue, Athena, Data
Engineering
Good to Have: Power BI/Tableau, PL/SQL, Agil