Business Consulting-Technical analyst with ETL,GCP using Pyspark at NTT DATA

Pune, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

23 Mar, 26

Salary

0.0

Posted On

23 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

GCP Expertise, PySpark Proficiency, Python Programming, Data Modeling, ETL, SQL, Big Data Concepts, Communication, Collaboration

Industry

IT Services and IT Consulting

Description

Req ID: 335249 NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now. We are currently seeking a Business Consulting-Technical analyst with ETL,GCP using Pyspark to join our team in Pune, Mahārāshtra (IN-MH), India (IN). You bring systems design experience with the ability to architect and explain complex systems interactions, data flows, common interfaces and APIs. You bring a deep understanding of and experience with software development and programming languages such as Java/Kotlin, and Shell scripting. You have hands-on experience with the following technologies as a senior software developer: Java/Kotlin, Spring, Spring Boot, Wiremock, Docker, Terraform, GCP services (Kubernetes, CloudSQL, PubSub, Storage, Logging, Dashboards), Oracle & amp; Postgres, SQL, PgWeb, Git, Github & amp; Github Actions, GCP Professional Data Engineering certification Data Pipeline Development: Designing, implementing, and optimizing data pipelines on GCP using PySpark for efficient and scalable data processing. ETL Workflow Development: Building and maintaining ETL workflows for extracting, transforming, and loading data into various GCP services. GCP Service Utilization: Leveraging GCP services like BigQuery, Cloud Storage, Dataflow, and Dataproc for data storage, processing, and analysis. Data Transformation: Utilizing PySpark for data manipulation, cleansing, enrichment, and validation. Performance Optimization: Ensuring the performance and scalability of data processing jobs on GCP. Collaboration: Working with data scientists, analysts, and other stakeholders to understand data requirements and translate them into technical solutions. Data Quality and Governance: Implementing and maintaining data quality standards, security measures, and compliance with data governance policies on GCP. Troubleshooting and Support: Diagnosing and resolving issues related to data pipelines and infrastructure. Staying Updated: Keeping abreast of the latest GCP services, PySpark features, and best practices in data engineering. Required Skills: GCP Expertise: Strong understanding of GCP services like BigQuery, Cloud Storage, Dataflow, and Dataproc. PySpark Proficiency: Demonstrated experience in using PySpark for data processing, transformation, and analysis. Python Programming: Solid Python programming skills for data manipulation and scripting. Data Modeling and ETL: Experience with data modeling, ETL processes, and data warehousing concepts. SQL: Proficiency in SQL for querying and manipulating data in relational databases. Big Data Concepts: Understanding of big data principles and distributed computing concepts. Communication and Collaboration: Ability to effectively communicate technical solutions and collaborate with cross-functional teams About NTT DATA NTT DATA is a $30 billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long term success. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity. We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a part of NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Visit us at us.nttdata.com Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client's needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees. NTT DATA recruiters will never ask for payment or banking information and will only use @nttdata.com and @talent.nttdataservices.com email addresses. If you are requested to provide payment or disclose banking information, please submit a contact us form, https://us.nttdata.com/en/contact-us. NTT DATA endeavors to make https://us.nttdata.com accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at https://us.nttdata.com/en/contact-us. This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you'd like more information on your EEO rights under the law, please click here. For Pay Transparency information, please click here.

Responsibilities

The role involves designing, implementing, and optimizing data pipelines on GCP using PySpark, as well as building and maintaining ETL workflows. Collaboration with data scientists and analysts to understand data requirements and translate them into technical solutions is also key.