Job Description

As a Senior Data Engineer, you will design, develop, and operate data platform components and data-intensive products. You will own significant data engineering work from requirements and design through implementation and production support, partnering with Data Engineering, Data Science, Cloud, DevOps, Application, Product, and client-facing teams to deliver reliable solutions that support business growth.

This is a hands-on role for an experienced engineer who can solve distributed-data challenges, contribute to sound technical decisions, support other engineers, and help bring emerging technologies into reliable production capabilities.

Responsibilities

- Design, develop, and maintain data pipelines, platform components, and data-intensive services.
- Own data engineering work from requirements and technical design through implementation, deployment, and production support.
- Contribute to data acquisition strategies, dataset contracts, acceptance criteria, quality standards, lineage, and lifecycle policies.
- Build scalable batch and real-time data pipelines, lakehouse architectures, and distributed processing solutions for high-volume workloads.
- Help evolve the data ecosystem to support growth in data volume, velocity, variety, and product complexity.




- Apply and improve reusable patterns for data ingestion, transformation, storage, orchestration, testing, observability, and delivery.
- Build production systems that meet expectations for reliability, security, performance, scalability, cost efficiency, and SLA-driven delivery.
- Contribute to operational practices for monitoring, incident response, failure recovery, replay, backfills, schema evolution, and disaster recovery.
- Partner with Data Science and ML teams to productionize ML, AI, and LLM-based workloads and integrate them into customer-facing products.
- Collaborate with Cloud, DevOps, Application, Security, Product, and client teams to deliver robust solutions for business and customer needs.
- Evaluate technologies and architectural patterns, contribute to technical proofs of concept, and recommend adoption based on measurable value.
- Document technical decisions, trade-offs, risks, and implementation approaches.
- Participate in technical reviews and help improve design, code quality, testing, maintainability, and production ownership.
- Support engineering roadmaps, hiring, and capability development across the data engineering discipline.

📌 Senior Data Engineer (Chennai)
🏢 Nielseniq
📍 Chennai