Data GCP- Wipro

Wipro; Hyderabad, Chennai, Bengaluru; Hybrid; INR 2,500,000 - 4,000,000; Full time

Benefits offered by this job

Work from office 3 days/week

Job summary

Wipro is seeking a Data Lead to join our multi-functional product engineering teams in India. You will design, implement, and optimize distributed data systems using Google Cloud, with emphasis on batch and streaming pipelines and data governance.

You will lead technical initiatives, drive data engineering best practices, and collaborate with stakeholders to align data solutions with business goals while leveraging modern cloud technologies like GCP, Kubernetes, and Kafka.

Qualifications

• Extensive experience designing, building and supporting distributed data systems.
• Proficient with GCP Data Products for storage, processing, analytics and ML.
• Hands-on experience building batch and streaming pipelines on Google Cloud.
• Strong automation with CI/CD pipelines and modern tooling.
• Proficiency in Python, SQL, Java, Scala or Go.

Responsibilities

• Design scalable, low-latency data systems meeting reliability standards.
• Set data engineering strategy and best practices.
• Collaborate with engineering leadership and stakeholders.
• Deliver data solutions across multiple entities within the group.
• Promote secure, high-quality data pipelines and data integrity.

Skills

GCP Data Products

Batch Data Pipelines

CI/CD

Python

SQL

Java

Scala

Go

Big Data

Kafka

Spark

Docker

Kubernetes

GCP

Cloud Platforms

Jenkins

GitHub

Spinnaker

Tools

Jenkins

GitHub

Spinnaker

Job description

Data Lead

Location :: Bangalore , Chennai , Hyderabad

Years of exp :: 8+

3 days' Work from office

Job Description Summary

About this opportunity :

Join our Team as a Data Lead. You'll work within multi-functional product engineering teams to deliver top-quality data capabilities, demonstrating your engineering expertise and cloud opportunities

What youll be doing:

• Implement scalable, resilient, low-latency data systems.
• Ensure systems meet performance and reliability standards.
• Collaborate with engineering leadership and stakeholders.
• Set technical strategy and best practices for data engineering.
• Deliver solutions for multiple entities within the group.
• Ensure alignment with business needs and cloud opportunities.
• Promote secure, high-quality data pipelines.
• Implement standards for data integrity and compliance.
• Identify and eliminate recurring issues through automation.
• Improve operational efficiency and reduce manual intervention.
• Provide guidance and technical leadership.

What youll need:

• Extensive industry experience in designing, building and supporting distributed systems and large-scale data processing systems in production with a proven track record.
• Expertise in GCP Data Products for storage, processing, analytics, and machine learning, enabling enterprises to manage, analyse, and derive insights from data at scale e.g. BigQuery, Dataflow, Cloud Storage, Pub/Sub, and Cloud Composer.
• Good hands on experience to Build Batch Data and Streaming Data Pipelines on Google Cloud
• Proven experience and knowledge of automation and CI/CD – Jenkins, GitHub & Spinnaker.
• Best practice coding/scripting experience developed in a commercial/industry setting (Python, SQL, Java, Scala or Go).
• Strong working experience with operational data stores, data warehouse, big data technologies and data lakes
• Experience in using distributed frameworks (Spark, Flink, Beam, Hadoop)
• Good knowledge of containers (Docker, Kubernetes etc) and experience with cloud platforms such as GCP, Azure or AWS.
• Strong experience working with (Real Time streaming), such as Kafka technologies.
• Clear understanding of data structures, algorithms, software design, design patterns and core programming concepts.
• Good understating of cloud storage, networking, and resource provisioning

And any experience of these would be really useful:

• Certification in GCP “Cloud Architect”, “Cloud Developer”, “Professional Data Engineer”

Certification in Apache Kafka (CCDAK)