**Req ID**: ******We are currently seeking a Software Development Advisor to join our team in CDMX, Ciudad de México (MX-CMX), Mexico (MX).
The Senior Data Engineer will design, build, and maintain robust, scalable data pipelines and platforms that enable analytics, AI/ML, and data products across the US and LATAM.Working within a multidisciplinary Agile team, this role transforms connected enterprise data into reliable, governed datasets and features that drive business insights and decision-making.The position is based in Mexico City and requires strong collaboration with distributed implementation teams based in USA.PREVIOUS EXPERIENCE- Technical:1.Cloud data warehouses and lakehouses (BigQuery, Databricks, Synapse)2.Modern transformation frameworks (dbt, Spark, SQL-based ELT patterns)3.Streaming frameworks and stream-to-batch architectures (Spark Structured Streaming, Flink)4.Feature store concepts and implementations (Feast, Tecton or equivalent)5.Data quality and observability tools (Colibra)6.Data security, privacy, and compliance best practices (encryption, masking, GDPR/LPDP considerations)7.API and microservice integration for data products (REST, gRPC)8.Containerization and orchestration (Docker, Kubernetes)9.Programming languages: Python, Scala,



or Java for data engineering workloads10.Familiarity with ML model deployment patterns and MLOps tooling - Databricks and Dataiku11.Knowledge of analytics/reporting stacks (Looker, Power BI, Tableau) and semantic layers- Language requirement: English (Fluent) Spanish (Fluent)SPECIFIC KNOWLEDGE1.Cloud data warehouses and lakehouses (BigQuery, Databricks, Synapse)2.Modern transformation frameworks (dbt, Spark, SQL-based ELT patterns)3.Streaming frameworks and stream-to-batch architectures (Spark Structured Streaming, Flink)4.Feature store concepts and implementations (Feast, Tecton or equivalent)5.Data quality and observability tools (Colibra)6.Data security, privacy, and compliance best practices (encryption, masking, GDPR/LPDP considerations)7.API and microservice integration for data products (REST, gRPC)8.Containerization and orchestration (Docker, Kubernetes)9.Programming languages: Python, Scala, or Java for data engineering workloads10.Familiarity with ML model deployment patterns and MLOps tooling - Databricks and Dataiku11.Knowledge of analytics/reporting stacks (Looker, Power BI, Tableau) and semantic layers"**About NTT DATA

📌 Software Development Advisor (Xico)
🏢 NTT DATA México DE C.V.
📍 Xico