Senior Data Engineer

At NIQ, we deliver the most complete and clear understanding of consumer buying behavior that reveals new pathways to growth. We are looking for a Sr Data Software Engineer to join our NIQ Activate Technology team in CDMX, Mexico. This is a remote work environment.

NIQ Activate is a leading provider of AI-powered customer analytics, personalization, and brand collaboration platform. Serving dozens of retailers and brands across the world using cutting-edge Big Data, real-time analytics, and data-science automation. Our solution is disrupting existing data & media monetization models by enabling retailers to remain in control of their revenue.

As a Data Software Engineer, you will be responsible for building new data solutions for our rapidly expanding customer base and working with the top data ingestion technologies, working with a team of amazing, diverse-minded, and bright people who make an impact, generate creative & innovative ideas, and take on new perspectives.

Responsibilities

Own end-to-end data flows from requirements and architecture through implementation and production operations, including Data acquisition, Data set acceptance criteria, and Data Science integration.; Design and build scalable batch and real-time data pipelines and lakehouse solutions with a focus on large-scale data processing.; Take responsibility to explore technologies to scale up the Data ecosystem to handle rapid Big Data growth.; Partner with Data Science to productionize ML/AI workloads and ensure smooth integration into products.; Collaborate with cloud, DevOps, application, and client teams to deliver robust, secure, and scalable solutions that solve meaningful business problems.; Evaluate and adopt new technologies and patterns to evolve the data ecosystem as scale and complexity grow.

Requirements

3+ years of hands-on Data Engineering building and operating production-grade Data Systems and Pipelines (Data-Intensive, Distributed Processing, Databases).; B.Sc. / M.Sc. in Computer Science, Computer Engineering, or equivalent.; Proficiency in Python, working proficiency in Scala.; Strong expertise with at least one major cloud provider (AWS, Azure, or GCP).; Strong experience with Big Data processing (Spark, DataBricks) and event streaming (Kafka).; Experience with orchestration and platform tooling such as Airflow, ability to build maintainable DAGs and operationalize workflows.; Strong SQL skills and experience with data storage systems plus at least one of: Data Lake/Lakehouse, columnar DB, or NoSQL systems.; Hands-on experience with containers and Kubernetes (Helm is a plus) and modern CI/CD practices.; Familiarity with LLM workflow frameworks (LangChain/LangGraph).; Proven experience designing, building, and owning production-grade data pipelines (batch and/or streaming), including reliability, backfills, and SLA-driven delivery.; Ability to learn new technologies and work in a dynamic fast-paced environment.; Result-driven, pragmatic, and innovative.; Strong analytical skills, with an open and proactive mindset to investigate, learn, and propose solutions, highly self-driven and self-taught.; Strong English communication skills, both written and verbal.

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 / 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.

Benefits

Flexible working environment; Volunteer time off; LinkedIn Learning; Employee-Assistance-Program (EAP)