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Resum del rol
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At Staffy, we are looking for a Databricks Engineer / Data Engineer to join our team and play a key role in building scalable, high-performance data platforms that support analytics, reporting, machine learning, and business-critical use cases.
In this role, you will be responsible for designing, building, optimizing, and maintaining modern data solutions using Databricks Lakehouse architecture, distributed processing technologies, and cloud-native services. You’ll collaborate closely with data engineers, analytics teams, cloud specialists, and business stakeholders to ensure reliable and high-quality data delivery across the organization.
This opportunity is ideal for someone passionate about data engineering, performance optimization, and building scalable systems in modern cloud environments.
Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, PySpark, SQL, and Delta Lake.
Build and optimize ETL/ELT workflows to ingest, transform, validate, and publish data from multiple structured and semi-structured sources.
Develop curated datasets and data models that support analytics, business intelligence, reporting, and downstream products.
Implement and maintain Lakehouse architectures, including bronze, silver, and gold layers.
Optimize Spark jobs for performance, reliability, scalability, and cost efficiency.
Work with cloud storage and data services across AWS, Azure, or GCP environments.
Support orchestration processes using tools such as Databricks Workflows, Lakeflow Jobs, Airflow, Azure Data Factory, or similar technologies.
Implement monitoring, logging, alerting, and data quality controls for production pipelines.
Collaborate with cross-functional teams to understand requirements and deliver scalable data solutions.
Apply governance, security, access management, and compliance best practices.
Participate in code reviews, documentation, testing, CI/CD practices, and deployment activities.
Troubleshoot performance bottlenecks, pipeline failures, and production issues.
5+ years of experience in Data Engineering roles.
4+ years of hands-on experience with Databricks, Apache Spark, PySpark, or Spark SQL.
Strong experience with Python and SQL.
Proven experience building and supporting production-grade ETL/ELT pipelines.
Experience working with Delta Lake, Parquet, Lakehouse architectures, and distributed processing systems.
Experience with at least one major cloud platform: AWS, Azure, or GCP.
Strong understanding of data modeling, data warehousing, and pipeline reliability concepts.
Experience working with Git, CI/CD workflows, and deployment practices.
Hands-on experience troubleshooting Spark performance issues and production data environments.
Strong communication and collaboration skills.
Databricks Certified Data Engineer Associate or Professional certification.
Experience with Unity Catalog, lineage, governance, and secure data-sharing solutions.
Experience with real-time or streaming solutions using Spark Structured Streaming, Kafka, Event Hubs, or Kinesis.
Experience with orchestration tools such as Airflow, dbt, Databricks Workflows, or Azure Data Factory.
Familiarity with cloud-native services such as Snowflake, Redshift, BigQuery, Azure Synapse, EMR, AWS Glue, or similar tools.
Experience with Terraform, Databricks Asset Bundles, Databricks CLI, or Infrastructure as Code practices.
Experience supporting analytics, machine learning, or AI/ML workloads.
Understanding of cost optimization, autoscaling, and cluster governance strategies.
Experience working in enterprise or regulated environments.
People First culture.
Free access to streaming platforms.
Free access to Spotify premium.
GYM discount.
Travel discount.
E-Learning discount.
Birthday-day
We are a young and fast-growing recruiting company with five years of experience working across Latin America and the United States. We partner closely with teams and founders to help them build strong, high-impact teams through recruitment, outsourcing, and team-building services.
Our culture is built on effective communication, trust, and transparency. We believe great work happens when people feel heard, supported, and empowered to grow. Today, our team is made up of more than 50 professionals working across different projects throughout the region, collaborating remotely and learning from each other every day.