Data Analyst - Data Lake Support

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• India - Bengaluru
• Information Technology
• No
• Regular Full-Time
• 2557
  
  

Emmes Global

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Overview

Job Description

Job Posting Title

India Remote/Ahmedabad/Bengaluru/New Delhi

Emmes Group: Building a better future for us all.

Emmes Group is transforming the future of clinical research, bringing the promise of new medical discovery closer within reach for patients. Emmes Group was founded as Emmes more than 47 years ago, becoming one of the primary clinical research providers to the US government before expanding into public-private partnerships and commercial biopharma. Emmes has built industry leading capabilities in cell and gene therapy, vaccines and infectious diseases, ophthalmology, rare diseases, and neuroscience.

We believe the work we do will have a direct impact on patients’ lives and act accordingly. We strive to build a collaborative culture at the intersection of being a performance and people driven company. We’re looking for talented professionals eager to help advance clinical research as we work to embed innovation into the fabric of our company. If you share our motivations and passion in research, come join us!

Primary Purpose

This position will support and optimize our data lake infrastructure and play a crucial role in ensuring the reliability, efficiency, and usability of our data lake environment

Responsibilities

• Responsible for the day-to-day management and maintenance of the data lake infrastructure, including data ingestion, storage, organization, and retrieval processes.
• Monitor and assess the quality of data stored in the data lake, identify inconsistencies, errors, and gaps, and collaborate with relevant stakeholders to address data quality issues.
• Develop and implement data integration and transformation pipelines to ingest, cleanse, and transform data from various sources into the data lake, ensuring compatibility and consistency.
• Develop and implement data integration and transformation pipelines to ingest, cleanse, and transform data from various sources into the data lake, ensuring compatibility and consistency.
• Implement and enforce data governance policies and security measures to safeguard sensitive and confidential data stored in the data lake, in compliance with regulatory requirements and best practices.
• Identify opportunities to optimize the performance and efficiency of the data lake infrastructure, including storage optimization, query performance tuning, and resource utilization monitoring.
• Conduct exploratory data analysis and perform ad-hoc queries to extract insights and derive actionable intelligence from the data lake, supporting decision-making processes across the organization.
• Maintain comprehensive documentation of data lake processes, configurations, and workflows, and generate regular reports on data lake performance, usage metrics, and data quality metrics.
• Collaborate with cross-functional teams, including data engineers, data scientists, business analysts, project managers, and internal/external IT professionals, to understand data requirements, prioritize initiatives, and deliver data solutions that meet business needs.
  
  

Qualifications

• Bachelor's degree or higher in Computer Science, Information Systems, Statistics, Mathematics, or a related field.
• Skilled in using Azure specific tools for data analysis, including Microsoft Fabric, Azure Synapse Analytics for big data and complex analysis tasks, and Microsoft Power BI for data visualization and business intelligence solutions.
• Proficiency in SQL and experience with database management systems (DBMS) for querying, manipulating, and analyzing large datasets.
• Strong analytical and problem-solving skills, with the ability to interpret complex data sets, identify patterns, and draw meaningful insights.
• Familiarity with data modeling concepts, data warehousing principles, and ETL (Extract, Transform, Load) processes.
• Experience with other cloud platforms like AWS and GCP is a plus.
• Excellent communication and interpersonal skills, with the ability to effectively communicate technical concepts to non-technical stakeholders.
• Strong attention to detail and a commitment to data accuracy, integrity, and security.
  
  

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