6 publicaciones de empleo destacadas de principal technical program manager, engineering enablement en ciudad de méxico (¡Están contratando!)

Data Architect
BMC Software —Ciudad de México, CDMX
- $1,470,000 a $2,450,000 por año
- Azure
- Salesforce
- SQL
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- Informática
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Salesforce Developer - Affirmative Action Vacancy for Women
Salesforce —Ciudad de México, CDMX
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- HTML
Operations Project Intern (TikTok LIVE-AMS-LATAM) - 2026 Start (BS/MS)
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- Inglés
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Data Architect

BMC Software -
Ciudad de México, CDMX

Postúlate ahora

Información del empleo

$1,470,000 a $2,450,000 por año

Cualificaciones

Looker
Power BI
Modelado de datos
Azure
Salesforce
NetSuite
Tableau
SQL
Seguridad
S3
Kafka
Python

Descripción completa del empleo

Basic Information

Job Name

Lead Data Scientist - Mexico

Country

Mexico

State

Ciudad de Mexico

City

Mexico City

Date Published

12-Jun-2026

Job ID

47111

Travel

You may occasionally be required to travel for business

Looking for details about our benefits?

Description and Requirements

Remote: #LI-Remote

BMC empowers nearly 80% of the Forbes Global 100 to accelerate business value, faster than humanly possible. Our industry-leading portfolio unlocks human and machine potential to drive business growth, innovation, and sustainable success. BMC does this in a simple and optimized way by connecting people, systems, and data that power the world’s largest organizations so they can seize a competitive advantage.

Title: Data Architect (Hands-On Builder)

Location: Mexico Remote

Data Architect will focus on the design, build, and evolve a modern, scalable data architecture that will power analytics, reporting, AI/ML use cases, and operational decision-making across the GTM business. This role will define data patterns and standards, partner with IT, and business partner teams to ensure our data platform is secure, reliable, cost-efficient, and easy to use.

This role is ideal for someone with strong hands-on architecture depth and can define target-state architecture, guide implementation, and ensure high-quality delivery across pipelines, integrations, and governance.

Key Responsibilities:

Build and Own Core Data Pipelines (Hands-On)
Architect and implement end-to-end ingestion and transformation pipelines from source systems into Snowflake.
Develop robust ELT/ETL workflows using dbt and orchestration tools (e.g., Airflow/Dagster/ADF), including:
incremental loads, SCD handling, backfills, and reprocessing
late-arriving data patterns and idempotent job design
CDC-based ingestion where applicable
Build integrations for key enterprise SaaS systems (Salesforce, Marketing Cloud, Netsuite, Zuora, Gainsight, CSOD) and internal app databases.
Data Modeling & dbt Development
Own the data modeling layer in Snowflake with dbt:
design dimensional models (star schemas), marts, and curated layers
marts, modular models, macros, packages
define metric-ready datasets (e.g., ARR/NRR, pipeline, churn, product usage) with consistent definitions
Optimize for performance and cost (clustering, warehouse sizing, query patterns, caching, micro-partitioning awareness).

Cloud Platform Enablement (AWS + Azure)

Implement secure, scalable data platform components across AWS and Azure:
landing zones, storage (S3/ADLS), networking, secrets management, and compute integration patterns
secure connectivity to Snowflake (PrivateLink/peering patterns where relevant)
Work with technology teams to implement RBAC, role hierarchy, masking policies, row access policies, and data sharing patterns.

Reliability, Testing, and Observability

Implement data quality and reliability controls:
dbt tests (schema, relationship, accepted values) and custom tests for business logic
anomaly detection and pipeline monitoring (e.g., Datadog/CloudWatch/Azure Monitor, Monte Carlo if applicable)
SLAs/SLOs for critical datasets and clear incident runbooks
Build operational readiness: logging, alerting, retries, failure isolation, and safe deploys.

CI/CD, Version Control, and Engineering Practices

Build and maintain CI/CD for data development (PR checks, dbt builds, environment promotion).
Establish practical engineering standards:
naming conventions, repo structure, branching strategy
documentation that stays current (dbt docs, data dictionaries)
code reviews and design patterns that scale with the team

AI / Agentic AI Architecture

Design and implement architecture patterns that support AI/ML, GenAI, and agentic AI use cases across the Sales business, including structured and unstructured data pipelines, retrieval-ready data design, and secure enterprise data access.
Define scalable patterns for AI-enabled applications and agents, including metadata design, indexing, vector-ready data preparation, API/tool access, and governance controls such as lineage, auditability, observability, and guardrails.
Partner Closely with Analytics & Business Teams
Collaborate with BI/Analytics to ensure the curated layer supports dashboards and self-service.
Translate business needs into data products quickly with tight feedback loops, iterative delivery, measurable outcomes.

Required Qualifications

10+ years of experience in data engineering and data architecture with a strong hands-on track record.
Strong production experience with Snowflake (performance tuning, data loading patterns, security model).
Strong production experience with dbt:
incremental models, snapshots, tests, macros, documentation, deployments
Experience building pipelines and integrations in AWS and/or Azure (both preferred).
Advanced SQL skills and strong understanding of data modeling (dimensional modeling, SCD types).
Experience with orchestration (Airflow, Dagster, Prefect, or Azure Data Factory) and reliable job design.
Strong understanding & framework implementation of data quality, monitoring, and operational best practices.

Preferred Qualifications (Nice to Have)

Experience with ingestion tooling (Boomi, Fivetran, Matillion, Informatica, Stitch) and/or CDC tooling (Debezium/HVR).
Experience designing or supporting data architecture for GenAI, RAG, enterprise search, or agentic AI use cases in production environments.
Familiarity with modern AI-related technologies and patterns such as OpenAI APIs, LangChain/LangGraph, Snowflake Cortex, Azure AI services, vector-ready data pipelines, and secure tool integration for AI agents.
Experience with streaming/event ingestion (Kafka/Kinesis/Event Hubs) for near-real-time pipelines.
Familiarity with governance/security patterns in Snowflake (masking/row access, tags, classification).
Exposure to BI layers (Tableau/Power BI/Looker) and semantic/metrics frameworks.
Python experience for custom integrations, APIs, and automation (Lambda, Azure Functions).

CA-DNP

Our commitment to you!

BMC’s culture is built around its people. We have 6000+ brilliant minds working together across the globe. You won’t be known just by your employee number, but for your true authentic self. BMC lets you be YOU!

If after reading the above, You’re unsure if you meet the qualifications of this role but are deeply excited about BMC and this team, we still encourage you to apply! We want to attract talents from diverse backgrounds and experience to ensure we face the world together with the best ideas!

BMC is committed to equal opportunity employment regardless of race, age, sex, creed, color, religion, citizenship status, sexual orientation, gender, gender expression, gender identity, national origin, disability, marital status, pregnancy, disabled veteran or status as a protected veteran. If you need a reasonable accommodation for any part of the application and hiring process, visit the accommodation request page.

BMC Software maintains a strict policy of not requesting any form of payment in exchange for employment opportunities, upholding a fair and ethical hiring process.

Min salary

1,470,000

Max salary

2,450,000

Postúlate ahora

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principal technical program manager, engineering enablement empleos en ciudad de méxico

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