Senior Databricks Data Engineer - Remote & Growth-Driven

AgileEngine, LLC.; Buenos Aires; Presencial; ARS 136.145.000 - 196.654.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Growth without limits

Competitive compensation

Flexibility: 100% remote

Meaningful, modern projects

Collaborative culture

Well-being & support

Descripción de la vacante

AgileEngine is seeking a Senior Data Engineer to transform a 15-year-old data warehouse into a governed Databricks Lakehouse. You will design batch and streaming pipelines with PySpark and Delta Lake, following a medallion architecture for analytics, reporting, and ML use cases.

The role involves migrating legacy workloads, applying AI tools like Claude and GitHub Copilot to accelerate development, and ensuring data quality and governance across the pipeline.

Formación

• 4+ years of professional experience in data engineering.
• Experience with Databricks, Apache Spark (PySpark), and Delta Lake.
• Advanced SQL and Python, with data modeling skills 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 managing data hygiene when porting old systems.
• Strong problem-solving, collaboration, and communication skills, including mentoring junior engineers and explaining data concepts to non-technical stakeholders.
• Familiarity with Unity Catalog, data governance, access control, and PII handling.
• Experience with dbt or an equivalent transformation framework.
• Familiarity with secure coding standards and industry security best practices.

Responsabilidades

• 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 machine learning consumers.
• Migrate legacy ETL and data warehouse workloads onto the Lakehouse with validated data parity and minimal business disruption.
• Use Claude or Github Copilot as a development accelerator, generating code scaffolding, writing and reviewing tests, creating documentation and prototyping solutions.
• Write clean, well-tested Python and SQL; maintain high standards through code review and documentation.
• Optimize Spark jobs and Delta tables for performance and cost, including partitioning, clustering, caching, and cluster sizing.
• Implement data quality, lineage, and governance controls using Unity Catalog and automated validation 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 best practices.

Conocimientos

Apache Spark

Databricks

Delta Lake

SQL

Python

Structured Streaming

Kafka

Databricks Workflows

Airflow

Azure Data Factory

Herramientas

Databricks

Airflow

Azure Data Factory

Terraform

CI/CD (Azure DevOps)

Delta Lake

Descripción del empleo

AgileEngine is seeking a Senior Data Engineer to transform a 15-year-old data warehouse into a governed Databricks Lakehouse. You will design batch and streaming pipelines with PySpark and Delta Lake, following a medallion architecture for analytics, reporting, and ML use cases.

The role involves migrating legacy workloads, applying AI tools like Claude and GitHub Copilot to accelerate development, and ensuring data quality and governance across the pipeline.