Manager, Azure & Databricks at IQVIA

Bengaluru, Karnataka, India

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Healthcare, TechnologyIndustries

Requirements

9-13 years of experience in Data warehousing or Data Engineer role
At least 4+ years of experience working with data and data analytics development within the Azure cloud platform
Accredited Cloud professional, strong into Azure Databricks, Azure Data Factory, Azure Data Lake, PaaS services
Experience with object-oriented/object function scripting languages: Python, PySpark, etc
Ability to configure and manage any Azure component pertaining to ETL/ELT processes (ADF, Azure SQL, Azure Data Lake, Databricks, Synapse, Logic Apps)
Expert level knowledge on SQL, database administration and data related programming elements (e.g., Python)
Hands-on experience to develop BI solutions using Snowflake, Databricks and Azure
In-depth understanding of data management (e.g., permissions, security, and monitoring)
Experienced in building and operationalizing large-scale enterprise data solutions and applications
Expertise in database development projects and ETL processes
Excellent analytical and organizational skills
Effective working in a team as well as working independently
Experience in an agile SDLC environment
Strong written and verbal communication skills

Responsibilities

Manages a team of professional-level employees
Develops and communicates plans and priorities to meet team performance and results requirements
Establishes team processes, goals, and procedures and tracks performance
Informs and influences decision-making at the management level
Provides coaching and guidance on job performance and career development to direct reports
Manage, troubleshoot, and extend architecture and implementation of data platforms including: ETL/ELT processes using Azure components
Working with business clients to understand their needs and to implement the cloud strategies designed to meet those needs
Develop batch processing, streaming and integration solutions
Manage source data access security
Configure authentication and authorization in Azure
Manage and enforce data policies and standards

Skills

Azure

Databricks

Snowflake

Azure Data Factory

Azure Data Lake

PySpark

Python

SQL

ETL

ELT

Azure Synapse

Logic Apps

PaaS

Data Warehousing

IQVIA

Advanced analytics and clinical research services

About IQVIA

IQVIA provides advanced analytics, technology solutions, and clinical research services specifically for the life sciences industry. Their services utilize extensive data resources and technology to create connections within healthcare, allowing clients to gain insights that help speed up the development and marketing of new medical treatments. This process is facilitated by their IQVIA Connected Intelligence™ system, which offers quick and flexible insights. IQVIA stands out from competitors by focusing on patient privacy, employing various technologies to protect individual data. The company's goal is to enhance healthcare outcomes by supporting biotech, pharmaceutical, and medical device companies, as well as researchers and government agencies, in understanding diseases and advancing medical science.

Durham, North CarolinaHeadquarters

1998Year Founded

$3,526MTotal Funding

POST_IPO_EQUITYCompany Stage

Cybersecurity, Biotechnology, HealthcareIndustries

10,001+Employees

Risks

Rapid advancement of cancer vaccines may disrupt traditional clinical research models.

Proliferation of disparate technological solutions causes technology overload in clinical trials.

Generative AI technologies face challenges in adoption due to data privacy concerns.

Differentiation

IQVIA leverages advanced analytics and big data for life sciences solutions.

The company offers privacy-enhancing technologies to protect individual patient data.

IQVIA's AI Assistant provides rapid, actionable insights for healthcare and life sciences.

Upsides

Increased adoption of decentralized clinical trials enhances patient-centric study designs.

AI-driven drug discovery accelerates identification of potential drug candidates.

Expansion of telemedicine facilitates remote patient monitoring and data collection.

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