Senior Databricks Engineer ID86295

AgileEngine; Ciudad de Mendoza; Híbrido; ARS 135.820.000 - 226.367.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

USD-based compensation

Flextime / hybrid work

Descripción de la vacante

AgileEngine in Argentina is seeking a Senior Data Engineer to build batch and streaming data pipelines on Databricks, migrating legacy ETL workloads to a governed Lakehouse.

You will model a medallion architecture (bronze/silver/gold) for analytics and AI use cases, using PySpark, Delta Lake, Unity Catalog, and SQL/Python data modeling across lakes and warehouses.

Join a people-first team with flextime and hybrid work options; compensation is USD-based and aligned with experience.

Formación

• 3+ years of professional data engineering experience.
• Expertise with Apache Spark, PySpark, and Delta Lake.
• Advanced SQL and Python with data modeling in lakehouse patterns.
• Experience with streaming ingestion and structured streaming.
• Experience with data governance and Unity Catalog.
• Upper-intermediate English level.

Responsabilidades

• Design and operate batch and streaming pipelines on Databricks using PySpark, Delta Lake, and Databricks Workflows.
• Model and maintain a medallion architecture for analytics, reporting, and ML.
• Migrate legacy ETL workloads to the Lakehouse with data parity and minimal disruption.
• Write clean, tested Python and SQL; contribute code reviews and documentation.
• Optimize Spark jobs and Delta tables for performance and cost.
• Implement data quality, lineage, and governance with Unity Catalog.
• Collaborate with DevOps, platform, and analytics engineers on observability and security.

Conocimientos

SQL proficiency

Python programming

English (Upper-Intermediate)

Herramientas

Databricks

Apache Spark (PySpark)

Delta Lake

Kafka / Event Hubs

Airflow / Databricks Workflows

Azure Data Factory

Descripción del empleo

Job Description

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE

We are looking for a Senior Data Engineer to build batch and streaming pipelines on Databricks using PySpark and Delta Lake. This person migrates legacy data warehouse and ETL workloads onto a governed Lakehouse, modeling a medallion architecture that powers analytics and AI use cases. Strong SQL, Python, and experience with Unity Catalog governance round out the role.

WHAT YOU WILL DO

• 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.
• Collaborate with DevOps, platform, and analytics engineers on observability, security, and compliance best practices.

MUST HAVES

• 3+ years of professional experience in data engineering , featuring direct expertise with Apache Spark and cloud-based data architectures .
• Strong hands-on experience building data pipelines with Databricks, Apache Spark (PySpark), and Delta Lake .
• Advanced SQL and Python , with strong 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 .
• 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 .
• Experience delivering production data platforms at scale .
• Upper-intermediate English level .

NICE TO HAVES

• Experience with Infrastructure as Code (IaC) using Terraform and CI/CD using Azure DevOps.
• Experience working with relational databases (specifically PostgreSQL) and data persistence concepts.
• Familiarity with logging and monitoring tools (e.g., Dynatrace, CloudWatch, Databricks system tables).
• Experience working in Agile or team-based development environments preferred.

PERKS AND BENEFITS

• Professional growth : Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.
• Competitive compensation : We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.
• A selection of exciting projects : Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.
• Flextime : Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.