Job Description
- Experience designing, building, and maintaining scalable data and API-driven applications, with a strong focus on cloud-native architectures.
- Proven expertise working within enterprise data warehouse and analytics ecosystems, analyzing and modeling complex cross-object and cross-domain data relationships.
- Demonstrated success as a hands-on individual contributor, owning end-to-end delivery across 2–3+ full software engagements—from requirements and architecture to deployment and production support.
- Strong proficiency in SQL, Python, and Java for data transformation, pipeline orchestration, backend services, and automation.
- Advanced experience using Java for Dataflow (Apache Beam) pipelines, API development, and microservices, with a solid grasp of object-oriented design, performance tuning, and error handling.
- Deep hands-on knowledge of Google Cloud Platform data services, including:
- Big Query for large-scale analytics and optimized query performance
- Pub/Sub for event-driven and streaming architectures
- Cloud Storage (GCS) for durable, cost-effective data storage
- Cloud Functions for lightweight, event-based processing
- Dataflow (Apache Beam) for batch and streaming data pipelines
- Experience designing and operating batch, streaming, and near–real-time pipelines, ensuring scalability, fault tolerance, schema evolution, and cost efficiency.
- Strong command of data quality and reliability engineering, including data validation, reconciliation, monitoring, and exception-handling strategies aligned with production-grade requirements.
- Hands-on experience validating RESTful APIs, covering schema integrity, payload validation, downstream data correctness, and performance SLAs.
- Exposure to validating analytics and visualization layers using Looker Studio and Tableau, ensuring accuracy and consistency between source systems, transformations, and dashboards.
- Working knowledge of graph databases and their applicability for modeling highly connected datasets (nice to have).
- Strong data engineering mindset, with the ability to design, simulate, test, and optimize real-world data scenarios across GCP environments.
- Comfortable working within Agile/Scrum delivery models, collaborating closely with cloud architects, product owners, data scientists, and DevOps/SRE teams.
- Alignment with Google Cloud Data Engineer best practices, including security, IAM, cost optimization, monitoring, and operational excellence.
Experience: 8-10 Years .
Reinvent your world. We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention.
Wipro is committed to creating an accessible, supportive, and inclusive workplace. Reasonable accommodation will be provided to all applicants including persons with disabilities, throughout the recruitment and selection process. Accommodations must be communicated in advance of the application, where possible, and will be reviewed on an individual basis. Wipro provides equal opportunities to all and values diversity.