Digital Next- Consultant

2 weeks ago

Gurgaon, Haryana, India KPMG India Full time
About KPMG in India

KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Jaipur, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada.

KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focused and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment.Qualification
BE/BTech with 4 to 6 years of experience.Learning Path Interventions:
Technical Trainings: A list of identified technical trainings is available to help perform the role better. Some of these trainings are mandatory and some are recommended courses.Enabling Skills: These are soft skill trainings to help you perform your role better and include trainings such as corporate etiquette, client interaction skills and writing effective emails.Equal employment opportunity information

KPMG India has a policy of providing equal opportunity for all applicants and employees regardless of their color, caste, religion, age, sex/gender, national origin, citizenship, sexual orientation, gender identity or expression, disability or other legally protected status. KPMG India values diversity and we request you to submit the details below to support us in our endeavor for diversity. Providing the below information is voluntary and refusal to submit such information will not be prejudicial to you.Knowledgeable in solution architecture and implementation of large and complex data analytics platforms, especially using Microsoft Azure services and other tools.Understanding of business requirements, translating them into technical designs, deal with complexities of integration of disparate systemsAnalyze and understand enterprise reporting needs across the organization. Identify and analyses source data (both internal and external) that is necessary to fulfil business intelligence needs.Experience in working with Azure Data Factory (ADF) and Azure Synapse Analytics for creating multiple pipelines and activities for full and incremental data loads into Azure Data Lake Store, Azure SQL DW and Azure Synapse DWWorking experience with Databricks, Spark framework as well as experience optimizing PySpark queriesExperience on Azure Data Lake Storage and working with CSV/ XML/ JSON/ Parquet files
Azure experience in designing and implementing redundant systems, policies, and procedures for disaster recovery and data archiving to ensure effective protection and integrity of data assetsDesign of conceptual/ logical/ physical entity relationship and/ or relational models and knowledge of Star and Snowflake multidimensional models for EDW/ DLDevelop, test, operate and support the end-to-end batch, near real time data and analytics solutionMust be familiar with building stream pipelines to leverage IoT Hub, Event Hub, Databricks streaming and other Azure stream technologiesPerforms thorough code reviews of fellow developers and ensure quality code. (Guide the development and maintenance of data standards, data models in alignment with the solution architecture.)Use DevOps knowledge, cloud and data engineering expertise to operate, monitor and troubleshoot the pipelines / code basesProactively collaborate and support the team if needed during the whole sprint cycleProvide technical design, coding assistance to the team to accomplish the project deliverables as planned/scoped.Work closely with Cloud administrator, DevOps manager, database administrator, ETL, and BI development staff to optimize overall design at an enterprise level.Formulates and recommends standards for achieving maximum performance and efficiency of the DW ecosystem.Setting development standards & producing design documentation & ensure other technical requirements such as performance, maintainability, and scalability

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