Data Engineer – Databricks

At Bridgenext, we engineer Growth Operating Systems. Most enterprises have spent millions on their revenue stack and still aren't seeing the growth they expected.They have tools that function, but no system that wins. We help growth-hungry companies close that gap by turning fragmented platforms, siloed teams, and disconnected data into one integrated Growth OS. More than a technology company or marketing agency, we're a global digital consultancy with experts in engineering, data, AI, creative and more.

Our teams are made up of experts who believe in engineering impact, starting with putting people at the center of everything we do. Every team member directly shapes our work, culture, and values. Nothing matters more to us than a kind, respectful, fulfilling environment that supports everyone. Our flexible, inclusive culture gives you the autonomy, resources, and opportunities to thrive.

We are looking for an experienced Data Engineer with strong hands-on expertise in Databricks to join one of our client's projects.

The ideal candidate must have solid experience building and maintaining data pipelines and data processing solutions using Databricks.

The most important requirement is that the candidate is currently working with Databricks in a production environment. Previous experience alone is not sufficient.

Responsibilities:

• Design, develop, and maintain scalable data pipelines using Databricks.
• Build and optimize ETL/ELT processes.
• Work with large datasets and distributed data processing.
• Develop and maintain data transformation workflows.
• Ensure data quality, reliability, and performance.
• Collaborate with engineering and business teams to support data requirements.

Workplace:  This is remote role, open to candidates based in Argentina or Columbia only

Must Have Skills:

• Active Databricks Expertise: Strong hands-on experience with Databricks, currently working with it in a production environment (non-negotiable).
• Data Pipeline & ETL/ELT: Proven experience designing, building, and optimizing scalable data pipelines using Apache Spark / PySpark and SQL.
• Architecture & Storage: Solid knowledge of Delta Lake and Data Lakehouse design patterns.
• Orchestration: Hands-on experience with Databricks Workflows or external orchestrators (e.g., Apache Airflow).
• Cloud Ecosystem: Practical experience integrating Databricks with at least one major cloud provider (AWS, Azure, or GCP) and its native storage/security services (e.g., S3, ADLS, IAM).

Preferred Skills:

• Modern Databricks Features: Experience with Delta Live Tables (DLT), Lakeflow, Unity Catalog, or Databricks SQL Warehouse.
• DevOps & CI/CD: Experience implementing CI/CD practices for data pipelines (e.g., Databricks Asset Bundles - DABs, GitHub Actions, Azure DevOps).
• Data Governance & Quality: Hands-on experience with data testing frameworks (e.g., Great Expectations, dbt) and data lineage.
• Certifications: Official Databricks Certifications (Data Engineer Associate or Professional).

Professional Skills:

• Advanced/Fluent English written and verbal communication skills
• Ability to work independently
• Excellent collaboration skills
• Strong analytical and problem-solving skills
• High standards of professionalism, consistently producing high quality results
• Self-sufficient, independent requiring very little supervision or intervention
• Passion for learning new technologies and staying current with industry trends
   

Bridgenext is an Equal Opportunity Employer