Senior Databricks Engineer Id86295

INGEPSY; Metropolitana; Presencial; COP 280.260.000 - 435.961.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive compensation

Curated projects

Flextime

Descripción de la vacante

AgileEngine is seeking a Senior Data Engineer to design, build, and operate batch and streaming data pipelines on Databricks, leveraging PySpark and Delta Lake to migrate legacy workloads to a governed Lakehouse. You will model a medallion architecture powering analytics, dashboards, and AI use cases.

The role requires strong SQL, Python, and experience with Unity Catalog governance, plus collaboration with DevOps and analytics teams to ensure performance, reliability, and data quality.

Formación

• 3+ years of professional data engineering experience with Spark and cloud data architectures.
• Strong SQL, Python, and experience with Delta Lake and Databricks.
• Experience migrating ETL workloads to Lakehouse with validated data parity.
• Familiarity with Unity Catalog governance and data quality practices.
• Ability to troubleshoot pipelines and collaborate with DevOps and analytics teams.

Responsabilidades

• Design, build, and operate batch and streaming data pipelines on Databricks (PySpark, Delta Lake).
• Model and maintain a medallion architecture serving analytics, reporting, and ML consumers.
• Migrate legacy ETL and data warehouse workloads onto the Lakehouse with minimal disruption.
• Use Claude or GitHub Copilot to generate scaffolding, tests, and documentation.
• Write clean Python and SQL and maintain high coding standards through reviews.
• Optimize Spark jobs and Delta tables for performance and cost.
• Implement data quality, lineage, and governance using Unity Catalog.
• Debug and resolve pipeline failures and production incidents.
• Collaborate with DevOps, platform, and analytics engineers on observability and security.

Conocimientos

Databricks

Apache Spark

PySpark

Delta Lake

SQL

Python

Data pipelines

Batch processing

Streaming processing

GitHub Copilot

Unity Catalog

Herramientas

Databricks

Airflow

Azure Data Factory

dbt

Descripción del empleo

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.

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.