October 8, 2024
By Umme Taiyaba
441
Jobs

Data Engineer Work From Home Job at Cognizant| Great Opportunity

Data Engineer Work From Home Job at Cognizant, ideal for the ones seeking to develop their careers in bendy surroundings. In this function, you’ll layout and put in force records answers, examine complex datasets, and collaborate with move-purposeful groups. With a focus on innovation and expert growth, Cognizant offers access to modern-day technologies and ongoing education. Join a dynamic crew and make contributions to impactful tasks at the same time as enjoying the blessings of far-flung paintings!

Job Title: Data Engineer Work From Home
Salary: Not Disclosed
Location: Anywhere, India
Company: Cognizant
Qualifications: Bachelor’s
Experience: 4-7 Years

ABOUT COGNIZANT

Cognizant is a multinational-era organization headquartered in Teaneck, New Jersey. Founded in 1994 as a division of Dun & Bradstreet, it has grown right into a main issuer of IT services and consulting. Cognizant makes a specialty of virtual transformation, cloud services, and statistics analytics, assisting groups to adapt to the unexpectedly evolving technological landscape.

With personnel of over three hundred,000 professionals, the organization serves customers across numerous industries, such as healthcare, finance, and manufacturing. Cognizant is known for its commitment to innovation, leveraging advanced technology like artificial intelligence and device studying to force enterprise efficiency.

Job Overview: Data Engineer Work From Home

Cognizant is seeking a Data Engineer for a far-flung role, accountable for designing, developing, and retaining statistics pipelines and architectures. The function includes collaborating with go-practical teams to optimize statistics go with the flow and make sure statistics are fine. Key obligations encompass statistics integration, transformation, and garage, making use of tools like SQL, Python, and cloud structures. The ideal candidate should have enjoyed statistics modeling and ETL strategies, along with robust analytical and trouble-fixing abilties. A background in big information technologies and familiarity with data visualization equipment is a plus.

Role and Responsibilities and Skills of Data Engineer Work From Home:

Data Pipeline Development: Create and control scalable and efficient data pipelines to facilitate the collection, processing, and garage of massive datasets. This consists of extracting facts from diverse resources, remodeling them into a suitable layout, and loading them into records warehouses or lakes.
Data Architecture Design: Collaborate with architects to design statistics fashions that align with commercial enterprise needs. This involves defining facts schemas, statistics storage solutions, and integration strategies to make certain ultimate statistics float.
ETL Processes: Develop and optimize Extract, Transform, Load (ETL) approaches to ensure well-timed and correct data availability. This consists of automating workflows and making sure that information is cleaned, enriched, and proven earlier than it reaches quit users.
Data Quality Assurance: Implement data great tests and validation tactics to ensure the integrity and accuracy of facts. Regularly monitor record flows for anomalies and paintings on resolution strategies to mitigate information-associated problems.
Collaboration: Work carefully with facts scientists, analysts, and enterprise stakeholders to understand their statistics needs and offer vital support. This includes gathering requirements, imparting technical understanding, and advising on excellent practices for statistics usage.
Big Data Technologies: Utilize massive data technologies along with Hadoop, Spark, and NoSQL databases to manipulate and process big volumes of unstructured and semi-structured facts.
Cloud Platforms: Leverage cloud computing platforms like AWS, Azure, or Google Cloud to lay out and enforce scalable records answers. This consists of deploying data garage solutions and managing records to get entry to permissions.
Documentation and Reporting: Maintain comprehensive documentation of statistics methods, architectures, and workflows. Provide every day updates and reports on data engineering projects to stakeholders.
Continuous Improvement: Stay up to date with rising trends and technology in information engineering. Proactively perceive opportunities for procedure improvements and suggest enhancements to current systems.