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In Accenture Applied Intelligence, we provide industry solutions, scaled Data & AI services powered by industry experts, and help clients to extract business value. Palantir provides the world’s leading software platform for data-driven operations and decision-making. It is trusted to solve an organization’s most complex, time-critical, and data-sensitive problems. Palantir Foundry accelerates the deployment of an organization’s business operations platform leading to large-scale adoption of data for driving everyday business outcomes. Accenture’s combination with Palantir can transform the value chain of enterprises by becoming data-driven to the core.
The Accenture Palantir Practice has a unique center within Accenture that focus on the design and implementation of analytics solutions on top of Palantir’s big data platforms.
The center is looking for highly motivated, passionate, proactive, and experienced industry experts who can manage multi-disciplinary teams in training, guiding, and deploying end-to-end analytics solutions. As a Data Engineering Lead, you need to coordinate with the Project Team in understanding client requirements and how they translate into application features in the Palantir platform.
Expectations from the role
• Connect to multiple data sources as per Data Model/ Architecture
• Data Cleaning & Preparations per Data Model/ Architecture
• Data transformation as per Data Model/ Architecture
• Define Data Ontology objects with scope, security, ownership, Data Quality monitoring
• Constant Data preparation support to Data Scientists, Ontology Experts, and Design/UI Expert
• Hands-on involvement in development, maintenance, and operation of data pipelines for processing high throughput molecular assay readouts e.g. genetic variation data from NGS and genotyping platforms, RNA-Seq, microarrays, proteomics platforms, etc.
• Lead a team of 4-6 years
• 4-6 years of software development experience.
• Expert and very good experience in Python.
• Prior experience especially in following Coding Standards, unit testing, and optimizations.
• Strong problem-solving/ analytical skills.
• Expert-level hands-on experience in Pyspark.
• Expert in Spark core and Spark SQL with substantial experience in designing and implementing scalable data pipelines in this framework.
• Preference for proven experience with big data technologies such as Hadoop, and Spark.
• Proficient with Git, Jenkins, Docker, and Singularity.
• Good exposure to at least one cloud ecosystem (AWS/ GCP/ Azure)
• Good Understanding of one of Cloud DE basics skills preferably AWS Components: Docker, Kubernetes, S3, Ethina
• Prior experience with Palantir Foundry is a plus and preferred.
• Understanding of Palantir modules like Data Connection, Data Protection and Governance, Data Lineage, Design and implement Ontology, Model Repository, Reports, Code workbook, and Code repository preferred
• Previous bioinformatics experience is a plus. This can be demonstrated through prior involvement in one or more aspects of handling NGS data, from primary to tertiary processing. Basic familiarity with key concepts in genetics and molecular biology would be seen as a plus.
• Overall understanding of Database space (Databases, Data Warehouses, Reporting, Analytics, Data Mesh).
• Very good communication skills and interpersonal skills.
• Very good domain knowledge.
• Open to learning new technologies in-line with organizational needs/direction.
• Self-driven and laser-focused on delivering outcomes with speed and agility.
• A master's degree in any related technology is advantageous.
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