Offer summary

Qualifications:

Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)., 3+ years of experience in managing AWS cloud infrastructure, including Databricks administration., Hands-on experience with Databricks and various AWS services., Proficiency in data engineering and ETL processes, with strong troubleshooting and analytical skills..

Key responsabilities:

Administer, configure, and optimize Databricks clusters and AWS infrastructure for data processing.

Design and implement scalable and secure cloud infrastructure on AWS.

Collaborate with data teams to build data pipelines and ensure integration with machine learning models.

Facilitate scrum ceremonies and maintain documentation for infrastructure and agile processes.

Job description

PharmaForceIQ is a US-based cutting-edge life sciences omnichannel marketing and analytics SaaS platform company that partners with pharmaceutical, biotech and other life sciences companies to help deliver the Right Message to the Right Physician through the Right Channel at the Right Time by deploying the power of advanced predictive analytics and machine learning. The company’s focus on the life sciences industry has generated deep expertise in the nuances and complexities involved in the use of life sciences data to make drug marketing more effective.

The Role

Databricks & AWS Infrastructure Management: - Essential

Administer, configure, and optimize Databricks clusters, Unity Catalog and services on AWS for large-scale data processing and analytics.
Design and implement scalable, highly available, and secure cloud infrastructure on AWS.
Implement best practices for data security, backup, and disaster recovery within the AWS and Databricks environments.
Troubleshoot and resolve Databricks, AWS infrastructure, and data pipeline issues.
Monitor infrastructure performance and proactively optimize cost and resource utilization.
Assist with compliance & audit efforts.

Data Engineering & Platform Management: - Essential

Work with data engineering teams to design and build data pipelines and ETL processes using Databricks, AWS Glue, and other AWS services.
Collaborate with data scientists and analysts to ensure smooth integration of data pipelines with machine learning models and reporting systems.
Ensure the successful implementation of data architectures that meet scalability, performance, and governance standards.
Develop and maintain best practices for data modeling, pipeline efficiency, and performance tuning in the cloud environment.

Scrum Master & Agile Leadership: - nice to have

Facilitate scrum ceremonies (standups, sprint planning, retrospectives, etc.) to ensure effective communication and collaboration within agile teams.
Help guide and mentor team members on Agile best practices, principles, and methodologies.
Remove obstacles that impede the team’s progress and foster an environment of continuous improvement.
Coordinate with stakeholders, track project progress, and manage sprint delivery to meet business requirements and timelines.
Ensure the team delivers high-quality solutions by maintaining a focus on both technical excellence and agile discipline.

Collaboration & Documentation: -A must

Work cross-functionally with development, data, and business teams to ensure alignment on requirements and expectations.
Create and maintain detailed documentation for infrastructure, data pipelines, and agile processes.
Ensure proper knowledge transfer within the team and foster a culture of continuous learning and improvement.

Ideal Profile

Required Qualifications

Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience).
3+ years of experience in managing AWS cloud infrastructure, including Databricks administration.
hands-on experience with Databricks, AWS services (S3, EC2, Lambda, EKS , MariadB, OpenSearch, ElasticCache(Redis) etc.), and cloud-native architectures.
Proficiency in data engineering and ETL processes, with a deep understanding of data pipelines, data lakes, and data warehousing.
Proven experience as a Scrum Master in Agile environments, with a solid understanding of Scrum frameworks and practices.
Experience working with DevOps tools ( Terraform.) and CI/CD pipelines.
Strong troubleshooting, analytical, and problem-solving skills.
Excellent communication and collaboration skills to interact with technical and non-technical stakeholders.

What's on Offer?