Senior Data Engineer

NielsenIQ
Chennai, Tamil Nadu, India

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. Qualifications
  • 7+ years of hands-on software or data engineering experience, including experience designing, building, and operating production-grade data systems.
  • Experience contributing to complex data initiatives across teams.
  • B.Sc. or M.Sc. in Computer Science, Computer Engineering, or an equivalent technical field, or comparable practical experience.
  • Strong understanding of data-intensive and distributed systems, including scalability, reliability, consistency, and performance trade-offs.
  • Strong proficiency in Python and working proficiency in Scala.
  • Strong expertise with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform.
  • Experience with large-scale data processing technologies such as Apache Spark and Databricks.
  • Experience designing and operating event-driven or streaming systems using technologies such as Apache Kafka.
  • Experience with workflow orchestration and platform tooling such as Apache Airflow, including maintainable DAGs and operational business-critical workflows.
  • Advanced SQL skills and strong experience with data modeling, query optimization, and data storage systems.
  • Hands-on experience with at least one of the following: data lake or lakehouse architectures; columnar or analytical databases; or NoSQL or distributed database systems.
  • Experience owning production-grade batch and/or streaming pipelines, including data quality, observability, schema evolution, backfills, recovery procedures, and SLA management.
  • Hands-on experience designing, developing, deploying, and operating production-grade microservices.
  • Hands-on experience with containers, Kubernetes, and modern CI/CD practices; experience with Helm is an advantage.
  • Familiarity with LLM application and workflow frameworks such as LangChain or LangGraph.
  • Ability to evaluate technologies, make sound technical decisions, and communicate trade-offs to engineering and non-engineering stakeholders.
  • Strong collaboration, mentoring, and technical communication skills.
  • Ability to work effectively in a dynamic, fast-paced environment while balancing platform improvements with near-term product delivery.
  • Pragmatic, results-driven approach and commitment to strong engineering fundamentals.
  • Strong written and verbal communication skills in English. Nice to Have
  • Experience with Delta Lake and/or Apache Iceberg; ML lifecycle tools such as MLflow.
  • Experience with Pandas/Polars and building data services/APIs (e.g., FastAPI).
  • Experience building LLM-powered agents or chat assistants (RAG, tool/function calling, workflow or multi-agent orchestration) using modern frameworks and platforms.
  • Infrastructure as Code (Terraform/Pulumi/CloudFormation) and cloud security fundamentals (IAM, secrets, encryption).
  • Experience with observability tooling (metrics/logging/tracing) and cost/performance optimization for distributed workloads.
  • Experience building applications with React and Node.js.

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Is this Senior Data Engineer job remote or onsite?

This is based in Chennai, Tamil Nadu.

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