Associate Data & Analytics Engineer

Clinical Care Options LLC

About The Position

Decera Clinical helps life sciences companies accelerate HCP adoption of breakthrough therapies through three divisions: Accredited Medical Education, HCP Insights, and Medical Communications. As the Scientific Activation™ company, Decera Clinical supports pharmaceutical and biotech partners in engaging HCPs with clear, credible information that strengthens clinical understanding and decision-making. With more than twenty years of experience across major therapeutic areas, Decera Clinical delivers trusted scientific engagement that helps HCPs move from evidence to action. Our Data & Analytics team plays a critical role in this transformation by building the pipelines, platforms, and insights that power intelligent decision-making and measurable impact across healthcare and education. We are seeking an Associate Data & Analytics Engineer to join our growing data team. This is a hands-on, cross-functional, and learning-oriented role that bridges data engineering, analytics, visualization, and emerging AI technologies. As an Associate Data & Analytics Engineer, you’ll help design, build, and maintain data pipelines and analytics systems that support our AI-driven healthcare and education initiatives. You’ll work across the full data lifecycle — from ingestion and transformation to visualization and delivery — enabling actionable insights that shape better patient outcomes and learner experiences. This role is ideal for someone with 1–3 years of experience (or equivalent academic background) who’s eager to grow within a mission-driven organization at the intersection of healthcare, data, and technology.

Requirements

Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, or a related field.
1–3 years of professional or academic experience in analytics, data engineering, or data visualization.
Proficiency in SQL and basic familiarity with Python or PySpark.
Hands-on experience with Power BI, Databricks, or similar BI and data platforms.
Strong analytical and troubleshooting skills, with attention to detail and data accuracy.
Ability to communicate findings clearly to both technical and non-technical audiences.

Nice To Haves

Experience with cloud data platforms (Azure, AWS, or GCP).
Familiarity with ETL/ELT processes and data modeling (e.g., star schema, medallion architecture).
Basic understanding of APIs, version control (Git), and CI/CD workflows.
Exposure to AI/ML concepts or interest in exploring their practical use in analytics.

Responsibilities

Support the design, development, and maintenance of data pipelines and integrations (e.g., using Databricks, SQL, or Python).
Transform raw data into clean, analytics-ready datasets following best practices for quality and performance.
Identify, investigate, and resolve data anomalies or quality issues in coordination with business and engineering teams.
Conduct exploratory analyses and create ad hoc or manual reports to support business questions and urgent needs.
Partner with stakeholders to interpret findings and translate data into actionable insights.
Maintain consistent documentation of data definitions, logic, and reporting standards.
Build and maintain interactive dashboards and visualizations in Power BI, Databricks Dashboards, or custom Data Apps.
Collaborate with stakeholders to define KPIs and ensure visualizations align with business goals.
Support the rollout and improvement of data applications that make analytics more accessible across the organization.
Participate in exploratory projects using AI, ML, or LLM tools to enhance data workflows and automate insights.
Assist with the development and evaluation of predictive models under senior guidance.
Research emerging tools and methods that can improve analytics efficiency and scalability.
Work closely with data engineers, scientists, and business teams to understand systems and improve processes.
Document workflows, share knowledge, and contribute to a culture of continuous improvement.
Take initiative to develop technical and business domain expertise over time.