**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 workloads
10. Familiarity with ML model deployment patterns and MLOps tooling - Databricks and Dataiku
11. Knowledge of analytics/reporting stacks (Looker, Power BI, Tableau) and semantic layers
- Language requirement: English (Fluent) Spanish (Fluent)
SPECIFIC KNOWLEDGE
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 workloads
10. Familiarity with ML model deployment patterns and MLOps tooling - Databricks and Dataiku
11. 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