Job Description
Must Have
You will be responsible for:
• Own the design, development, and optimization of scalable data pipelines using AWS Glue to enable reliable ingestion and transformation of large-scale datasets
• Collaborate with product owners, analytics teams, and business stakeholders to translate data and analytics requirements into robust Snowflake-based solutions
• Design, implement, and maintain efficient data models (Lakehouse patterns) to support evolving analytical and business needs while ensuring performance and data integrity
• Build, enhance, and migrate complex ETL/ELT pipelines leveraging Snowflake, Delta Lake, Spark, and cloud object storage
• Continuously improve performance, scalability, reliability, and cost efficiency of data pipelines through code optimization, cluster tuning, and best practices
• Extract, transform, and integrate data from heterogeneous data sources, including structured, semi-structured, and unstructured data
• Take ownership across the end-to-end data lifecycle including analysis, design, development, testing, deployment, monitoring, and production support
• Process and analyze large-scale datasets using python, SQL and DBT to enable downstream analytics, reporting, and advanced use cases
• Implement and adhere to data governance, data quality, security, and compliance standards, ensuring proper documentation, lineage, and auditability within the Lakehouse
• Act as a technical owner for assigned data domains or pipelines, ensuring timely delivery and adherence to engineering standards
• Apply domain knowledge in pharma commercial analytics including brand, customer, omnichannel, and content performance data
• Enable the creation of actionable KPIs and analytical datasets for marketing, brand, and digital operations teams
Your impact: Candidate should be able to deliver cross functional projects with highest quality, mentor team to create next layer of leadership.
About you: (Desired profile)
We are seeking a dynamic and experienced Data Engineer to lead our talented team of data engineers/data analyst. In this role, you will be instrumental in shaping the architecture and infrastructure of our data systems, driving innovation, and ensuring the delivery of high-quality solutions. You will play a critical role in designing and implementing scalable data pipelines, optimizing data workflows, and leveraging advanced analytics techniques to drive business value. Pharma background preferred. Team management preferred.
Requirements:
• 3+ years of overall experience in data engineering with strong hands-on ownership of data pipelines
• Proven experience in ETL/ELT development, data modeling, and modern data architectures
• Strong ability to work with stakeholders and translate business requirements into technical solutions
• Experience working with Life Sciences / Pharma data is a strong advantage
• 4+ years of hands-on experience with AWS Glue and Snowflake including snow pipe, Snowpark, Cortex, Snowflake SQL and Delta Lake
• Hands-on experience with cloud object storage S3 integrated with Snowflake
• Strong programming experience in Python for data engineering use cases
• Advanced SQL skills, including complex joins, window functions, and performance tuning
• Experience working with Veeva CRM, Salesforce and relation databases such as MS SQL Server, Oracle, PostgreSQL or MySQL
• Understanding of data quality, governance, and security concepts in enterprise data platforms
• Excellent problem-solving, analytical, and communication skills, with the ability to independently deliver complex tasks
Good to have
• Exposure to ML/AI
• Understanding on Gen-AI & Agentic AI