Senior Databricks Data Engineer - Remote Lakehouse

AgileEngine; Mexico; Hybrid; MXN 900,000 - 1,500,000; Full time

Benefits offered by this job

Growth without limits

Competitive compensation

Flexibility

Meaningful, modern projects

Collaborative culture

Well-being & support

Job summary

AgileEngine is seeking an experienced Senior Data Engineer to help modernize a 15-year-old data warehouse into a governed Databricks Lakehouse. You will design and implement batch and streaming pipelines using PySpark, Delta Lake, and Databricks Workflows for analytics and ML consumers.

You will collaborate with DevOps and analytics engineers, apply data governance with Unity Catalog, and leverage AI tools like Claude and GitHub Copilot to accelerate development.

Qualifications

• 4+ years of professional experience in data engineering, with Spark and cloud-based architectures.
• Strong hands-on experience building data pipelines with Databricks, Spark (PySpark), and Delta Lake.
• Advanced SQL and Python and data modeling across dimensional and Lakehouse patterns.
• Experience with streaming ingestion using Structured Streaming, Auto Loader, Kafka, or Event Hubs.
• Experience with workflow orchestration (Databricks Workflows, Airflow, or Azure Data Factory).
• Experience with legacy platform migrations, ETL modernization, or data hygiene projects.
• Strong problem-solving, collaboration, and ability to explain data concepts to non-technical stakeholders.
• Familiarity with Unity Catalog, data governance, access control, and PII handling.
• Experience with dbt or equivalent transformation framework.
• Familiarity with secure coding standards and industry security best practices.

Responsibilities

• Design, build, and operate batch and streaming data pipelines on Databricks using PySpark, Delta Lake, and Databricks Workflows.
• Model and maintain a medallion (bronze/silver/gold) architecture serving analytics, reporting, and ML consumers.
• Migrate legacy ETL and data warehouse workloads onto the Lakehouse with validated data parity and minimal disruption.
• Use Claude or Github Copilot as a development accelerator, generating code scaffolding, tests, documentation, and prototypes.
• Write clean, well-tested Python and SQL; maintain high standards through code reviews and documentation.
• Optimize Spark jobs and Delta tables for performance and cost (partitioning, clustering, caching, sizing).
• Implement data quality, lineage, and governance using Unity Catalog and automated checks.
• Debug, troubleshoot, and resolve pipeline failures, data defects, and production incidents.
• Participate in Agile or product-centric delivery practices including sprint planning and retrospectives.
• Collaborate with DevOps, platform, and analytics engineers on observability, security, and compliance.

Skills

Databricks

Apache Spark (PySpark)

Delta Lake

SQL

Python

Structured Streaming

Kafka

Airflow

Databricks Workflows

Unity Catalog

dbt

Tools

Airflow

Azure Data Factory

Terraform

Databricks

PostgreSQL

Job description

AgileEngine is seeking an experienced Senior Data Engineer to help modernize a 15-year-old data warehouse into a governed Databricks Lakehouse. You will design and implement batch and streaming pipelines using PySpark, Delta Lake, and Databricks Workflows for analytics and ML consumers.

You will collaborate with DevOps and analytics engineers, apply data governance with Unity Catalog, and leverage AI tools like Claude and GitHub Copilot to accelerate development.