Clinical Data Engineer - 100% Remote/ W2

the pharma & health industry to accelerate the discovery, development, and manufacturing of new drugs, therapies, and vaccines - to save lives faster! This is an exciting opportunity to support pharmaceutical and biotech companies deploying innovative scientific R&D technologies globally. You will enable R&D Digital Transformation, design efficient data pipelines using the latest in Big Data Cloud Infrastructure and engineer new data analytics/visualization capabilities. You will empower our clients to build their future data landscape for data-driven decisions.

Responsibilities:

• Identify and analyze business needs to determine data related requirements,
• Clean, transform, and organize big data for analysis,
• Conduct data analysis to identify trends, patterns, and insights,
• Develop data visualization tools to communicate insights,
• Provide consulting inputs for guidelines, design ideas, standards, & best practices,
• Help stakeholders to estimate, plan, and prioritize data engineering efforts,
• Build relationship with clients, internal and partners' leadership team,

Requirements:

<>Required Skills:

• Experience with Clinical Data is a must have
• Expertise in Python, Spark, Java, Scala for building data pipelines, warehouses, and data processing systems,
• Expertise in relational databases like SQL & NoSQL,
• Strong understanding of NoSQL databases like MongoDB, Cassandra, and HBase,
• Familiarity with data standards such as FAIR, JSON, OWL and markup languages such YAML
• Understanding of AI/ML, data science concepts & cloud architecture

<>Preferred Skills:

• Bachelor's or Master's degree in data engineering / computer science or related field
• Experience with scientific informatics solutions OR background in biological science, chemistry, health sciences OR an experience working in the life or health science industry,
• Experience in cloud computing platforms like AWS, Azure, and Google Cloud Platform (Google Cloud Platform) for deploying and managing data infrastructure in the cloud,
• Experience using version control systems like Git for collaborative code development,
• Experience in data focused solutions such as Snowflake, Databricks, Kafka, Cloudera, Knime, Airflow, etc.
• Experience with AI/ML & data science libraries like Scikit-Learn, TensorFlow, PyTorch, HuggingFace, etc. for preparing data for downstream AI/ML applications,
• Familiarity with data visualization solution like Tableau, Power Bi and D3.js,
• Data engineering related certification from cloud platform like Azure/AWS/Cloudera,
• Customer centricity to deliver at the highest standards and elevate customer experience.