We are seeking a
Senior Databricks Architect
to own the target-state design of enterprise-scale lakehouse platforms and to act as the trusted technical authority for our clients' data modernization programs.
This is not a delivery-only engineering role. You will shape architecture before code is written: running discovery and assessment of legacy estates, defining reference architectures and migration roadmaps, setting platform standards, and defending design decisions in front of enterprise architecture boards, CISOs, and business sponsors. You will remain hands-on enough to prototype, unblock delivery teams, and prove that your designs work in production.
You will work across regulated and data-sensitive industries (financial services, banking, insurance, energy, retail), where security, governance, auditability, and cost predictability are as important as raw performance.
Key Responsibilities
Define
target-state lakehouse reference architectures
on Databricks, including medallion (bronze/silver/gold) design, workspace topology, environment segregation (dev/test/prod), and multi-region / multi-tenant patterns
Produce architecture artifacts that survive client review: solution blueprints, data flow and integration diagrams, Architecture Decision Records (ADRs), non-functional requirements, and risk registers
Select the right patterns for each workload — batch vs.
Structured Streaming / Auto Loader / Lakeflow Declarative Pipelines (DLT)
, classic vs. serverless compute, Delta Lake / Iceberg interoperability (UniForm)
Define
data modeling standards
(dimensional, Data Vault, domain/data-mesh-oriented data products) and semantic-layer strategy for downstream BI consumption
Lead
discovery and assessment
of legacy estates (Teradata, Netezza, Oracle/Exadata, SQL Server,



Hadoop/Cloudera, Informatica, SSIS, Synapse, Snowflake) — inventory, complexity scoring, dependency mapping
Build
migration roadmaps and wave plans
, including effort estimation, sequencing, coexistence/dual-run strategy, cutover and rollback plans
Establish reconciliation and data-validation frameworks so the business can trust the migrated platform
Requirements
8+ years
in data engineering, data platform, or cloud analytics roles
4+ years hands-on with Databricks
, including
2+ years in an architect or lead design capacity
Proven ownership of at least one
end-to-end enterprise lakehouse implementation or large-scale migration
from assessment through production
Expert-level
Spark (PySpark/Scala)
,
Python
, and
advanced SQL
; deep understanding of distributed processing, query optimization, and performance troubleshooting
Deep
Delta Lake
expertise (ACID, time travel, OPTIMIZE/VACUUM, schema evolution, CDC/CDF)
Production experience with
Unity Catalog
governance design, not just usage
Strong hands-on background in at least one major cloud —
Azure preferred
(ADLS Gen2, Data Factory, Entra ID, Key Vault, networking) — with working knowledge of AWS or GCP equivalents
Practical experience with
IaC (Terraform), CI/CD, and DevOps practices
for data platforms
Demonstrated ability to lead
client-facing workshops
and present and defend architecture to senior technical and business stakeholders
Excellent written and verbal communication; able to produce client-grade documentation
Preferred:
Databricks Architect certification
Team leadership experience
Migration/modernization project background
Why Join?
Competitive compensation, up to 100k MXN per month
High-impact enterprise projects
Remote work

📌 Senior Databricks Architect (México)
🏢 KWA Analytics
📍 México