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