Data Engineer

Key Skills

Aartificial intelligence, AI technology, Common data structures, Computer Vision (CV), Data Governance, Data Modeling, Data pipelines, Data science techniques, Data Warehousing, ETL/ELT technologies, Machine learning techniques, Mathematics, NumPy, Pandas, Python Programming, R Programming, Scala Programming, Scikit-learn, SQL, Statistics

Job Description

Accelerate drug discovery and development for Biopharma and Biotech R&D with in silico solutions leveraging Computational Biology & Chemistry, High throughput Sciences, AI, ML, HPC, Cloud, Data, and DevOps.

In silico solutions are transforming the biopharma and biotech industries. Our cross-domain science and technology team of experts embark upon and industrialize this transformation. We continually expand our world-class multi-disciplinary team in Genomics, AI and Cloud computing, accelerating drug discovery and development. What drives us is the joy of working in an innovation rich, research powered startup bridging multiple disciplines to bring medicines faster for human use. We are working with several innovative Biopharma companies and expanding our client base globally. Read about how and what solutions we build.

Key Responsibilities

Work with R&D teams of our Biopharma clients, and collaborate with a team of Biologists, Medicinal Chemists, Computational Chemists, Data Scientists, Data Engineers, Web Developers, Cloud Engineers, and Solution Architects to create the next generation of innovative computational biology solutions for drug discovery and development.

• Perform data modeling, visualization, and analysis using both relational and NoSQL database platforms
• Build data pipelines with Apache Spark
• Perform data mining using SQL query skills, MicroStrategy and workflow designers
• Identify, analyze, and interpret trends or patterns in complex data sets
• Assist in analytics integrations and ensure accurate data collection
• Implement / deploy large, structured, and unstructured databases based on scalable cloud infrastructures
• Port data across data-sources / DB systems to improve performance, scalability, and or to facilitate analytics.
• Develop technical solutions which combine disparate information to create meaningful insights for business, using Big-data architectures (supportive role along with Data Architect)
• Architect and develop data pipelines to optimize for performance, quality, and scalability
• Collaborate with data, engineering, and business teams to build tools and data marts that enable analytics
• Develop testing and monitoring to improve data observability and data quality
• Partner with data science to build and deploy predictive models
• Support code versioning, and code deployments for data pipelines

Desired Skills / Expertise

• Bachelor's in Computer Science or related technical field
• Extensive experience in areas such as:
• Querying SQL and/or NoSQL databases
• Data pipelining with Apache Spark
• Pipeline development with modular, typed, and object-oriented Python programming
• Managing data using APIs
• Semantic Intelligence and Knowledge Graph
• Manipulating data using scripting languages and/or data processing software (e.g., Python, R, Pipeline Pilot)
• Profiling data, summarizing, and reporting data quality metrics
• Expertise in SQL and data analysis and experience with at least one programming language (Python or Scala preferred)
• Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space (preferred)
• Experience with advanced technology tools like Python with Pandas /Numpy /Scikit
• Conceptual knowledge of data and analytics, such as dimensional modeling, ETL, reporting tools, data governance, data warehousing, structured and unstructured data
• Exposure to machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics
• Excellent communication skills with a desire to work in multidisciplinary teams