Azure data engineer

Hi {fullName}

There is an opportunity for AZURE DATA ENGINEER IN NOIDA

(Experience Strictly 4-10 years)

for which WALKIN interview is there on 12th JULY 25 between 9:30 AM TO 12:30 PM

PLS SHARE below details to mamidi.p@tcs.com with subject line as AZURE DATA ENGINEER 12TH JULY 25

if you are interested

Email id:

Contact no:

Total EXP:

Preferred Location:

CURRENT CTC:

EXPECTED CTC:

NOTICE PERIOD:

CURRENT ORGANIZATION: HIGHEST QUALIFICATION THAT IS FULL TIME :

HIGHEST QUALIFICATION UNIVERSITY:

ANY GAP IN EDUCATION OR EMPLOYMENT:

IF YES HOW MANY YEARS AND REASON FOR GAP:

ARE U AVAILABLE FOR WALKIN INTERVIEW AT NOIDA ON 12TH JULY 25(YES/NO):

We will share a mail to you by tom Night if you are shortlisted.

Pls find JD metioned below

Responsibilities:

• Data Pipeline Design and Development: Collaborate with data scientists, analysts, and other stakeholders to understand data requirements. Design, develop, and implement efficient data pipelines, integrating various data sources to transform raw data into usable formats.
• Cloud Data Platform: Utilize your expertise in working with cloud-based data platforms, especially Azure, to architect, deploy, and maintain scalable and reliable data infrastructure.
• Databricks Expertise: Demonstrate a strong understanding of Databricks and its capabilities, using it as a primary platform for big data processing, analytics, and machine learning.
• Data Modelling: Create and optimize data models that support data analytics, reporting, and visualization needs. Ensure data integrity, accuracy, and consistency.
• Performance Optimization: Continuously monitor and fine-tune data pipelines and processing workflows to enhance overall performance and efficiency, considering large-scale data sets.
• ETL (Extract, Transform, Load) Processes: Implement ETL processes to extract data from diverse sources, transform it into suitable formats, and load it into the data warehouse or analytical systems.
• Data Security and Compliance: Ensure data security and compliance with data privacy regulations throughout the data engineering process.
• Collaboration: Work closely with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements, share insights, and provide technical support.
• Troubleshooting and Issue Resolution: Proactively identify data-related issues and provide timely resolutions to maintain smooth data operations.

Documentation: Maintain comprehensive documentation for data pipelines, architecture, and processes, making it easier for team members to understand and contribute to the data engineering initiatives

Thanks & Regards

Priyanka

Talent Acquisition Group

Tata Consultancy Services