Title: Data Engineering Lead
KA, IN
Job Description
We are a technology-led healthcare solutions provider. We are driven by our purpose to enable healthcare organizations to be future-ready. We offer accelerated, global growth opportunities for talent that is bold, industrious and nimble. With Indegene, you gain a unique career experience that celebrates entrepreneurship and is guided by passion, innovation, collaboration and empathy. To explore exciting opportunities at the convergence of healthcare and technology, check out www.careers.indegene.com
What if we told you that you can move to an exciting role in an entrepreneurial organization without the usual risks associated with it?
We understand that you are looking for growth and variety in your career at this point and we would love you to join us in our journey and grow with us. At Indegene, our roles come with the excitement you require at this stage of your career with the reliability you seek. We hire the best and trust them from day 1 to deliver global impact, handle teams and be responsible for the outcomes while our leaders support and mentor you.
We are a profitable rapidly growing global organization and are scouting for the best talent for this phase of growth. With us, you are at the intersection of two of the most exciting industries of healthcare and technology. We offer global opportunities with fast-track careers while working with a team that is fuelled by purpose. The combination of these will lead to a truly differentiated experience for you.
If this excites you, then apply below.
Role: Tech Lead
Description
The Data Engineering Lead is a senior-level position within our Data Engineering team, responsible for spearheading the design, implementation, and optimization of advanced data architectures using Databricks. This role involves leading a team of data engineers, collaborating with business and data analysts, and business stakeholders, and delivering scalable, secure data solutions tailored to the needs of commercial analytics in the pharmaceutical industry.
Must Have
Responsibilities
1. Architecture Design
o Develop and maintain scalable data architectures using Databricks, including data lakes, data warehouses, and real-time processing systems.
o Create detailed blueprints for data processes and flows, ensuring alignment with business objectives.
2. Pipeline Development
o Design and implement ETL/ELT pipelines using Databricks and Apache Spark to process large-scale datasets efficiently.
o Optimize pipelines for performance, scalability, and reliability.
3. Data Governance
o Implement and enforce data governance policies, security measures, and compliance standards within the Databricks environment.
4. Collaboration
o Partner with data scientists, business analysts, and business stakeholders to understand data needs and deliver solutions that drive business value.
o Communicate complex technical concepts clearly to diverse audiences, fostering alignment and collaboration.
5. Integration
o Integrate Databricks with cloud services (e.g., AWS S3, Azure Data Lake Storage, Google Cloud Storage) and CRM/marketing automation platforms (e.g., Salesforce, Veeva) for seamless data flow.
o Ensure interoperability with existing systems to create a cohesive data ecosystem.
6. Innovation
o Stay updated on advancements in Databricks, Delta Lake, Databricks SQL, and related technologies, applying best practices to enhance data capabilities.
o Drive continuous improvement in data processes and tools.
7. Leadership and Mentoring
o Lead the implementation and optimization of Databricks for commercial pharma analytics, tailoring solutions for sales, marketing, and patient outcomes.
o Train and mentor team members on Databricks and analytics platforms, fostering a culture of data literacy and innovation.
8. Analytics Collaboration
o Collaborate with analytics teams to develop reporting frameworks for monitoring KPIs, such as engagement rates and campaign ROI.
o Ensure seamless integration of Databricks with CRM and marketing automation systems to support analytics workflows.
Desired Profile:
• 12+ years of experience in data engineering, with a strong focus on Databricks, Apache Spark, and cloud platforms (AWS, Azure, or GCP).
• Proficiency in Databricks, Python, Scala, SQL, and experience with ETL/ELT tools and pipeline orchestration (e.g., Apache Airflow, ADF).
• Pharma knowledge especially around entity HCP & HCO
• Data modeling/Medallion
• ETL/ELT pipeline design
• Data privacy/security
• Pharma entity (HCP/HCO) integration
• Deep knowledge of data modeling, schema design, and database management.
• Proven leadership in managing data engineering teams and projects, with strong project management skills.
• Excellent communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
• Strong understanding of syndicated data in pharmaceuticals.
• Experience in commercial pharma analytics is highly preferred.
• Bachelor’s degree in computer science, Data Science, or a related field; advanced degree (e.g., Master’s) is a plus.
• Certifications in Databricks, AWS, Azure, or related technologies is REQUIRED.
Good to have
EQUAL OPPORTUNITY