Senior data engineering and architecture

I design modern data platforms that turn complex migrations into reliable delivery systems.

Experienced Computer Engineer specialized in lakehouse architecture, Snowflake ecosystems, Databricks pipelines and legacy-to-cloud modernization across AWS and Azure.

Available for consulting, architecture and delivery leadershipSpanish native · Advanced English

16+

years working across engineering, analytics and modern data platforms

AWS · Azure

cloud environments used to modernize legacy ecosystems and operational pipelines

Batch + Real time

experience building reliable pipelines with Spark, Kafka, Snowflake and Databricks

Cristian Muñoz Rosenfeld

Lakehouse delivery playbook

Modernization mindset across batch, streaming, migration validation, orchestration and cloud-native execution.

Professional overview

Architecture with delivery discipline.

I combine hands-on engineering with architecture thinking, helping teams modernize data ecosystems without losing control of quality, standards or execution speed.

My background includes Data Lakehouse implementations, Hadoop and database migrations, cloud-native ETL and ELT, and scalable pipelines built with Python, PySpark, Snowflake, Databricks, Glue, Kafka and Airflow.

I work comfortably between strategy and execution: defining zones, standards, orchestration models, validation frameworks and release practices that keep data platforms maintainable as they scale.

Data LakehouseMigration ArchitectureSnowflakeDatabricksApache SparkKafkaAWSAzure

Modernization flow

Legacy data into cloud-native delivery.

Sources

Hadoop, SQL Server, BigQuery, APIs and Kafka

Ingestion + Validation

Glue, Spark, DLT, QA frameworks and schema checks

Lakehouse Core

Databricks, Delta Lake, zones, standards and orchestration

Serving Layer

Snowflake, warehousing, analytics consumption and scalable access

01

Modernization roadmaps

From Hadoop, BigQuery, SQL Server or Teradata into modern stacks that reduce operational friction and improve scalability.

02

Platform standards

Definition of landing, staging and trusted zones, pipeline best practices, validation flows and engineering conventions for growing teams.

03

Reliable delivery

Automation using Docker, CI/CD, Git workflows, orchestration tools and testing-oriented approaches to keep releases predictable.

Technical capabilities

A stack built for platform work, not just isolated pipelines.

My strongest value is connecting architecture, implementation and operational quality across the data lifecycle.

01

Engineering

PythonSQLPySparkFastAPIUnix scriptingDocker

02

Data platforms

SnowflakeDatabricksDelta LakeDLTLakehouse FederationData Catalog

03

Cloud and orchestration

AWS GlueStep FunctionsAthenaEMRLambdaAirflowPrefect

04

Streaming and storage

KafkaKSQLDBHadoopHivePostgreSQLSQL ServerMongoDB

Contact

If you need migration leadership, platform architecture or senior delivery support, let's connect through WhatsApp.

WhatsApp is the primary contact channel here. You can also use the links below for direct contact.