Data Engineer - Databricks Data Platform & Pipelines

Klanik; Miami (FL); On-site; USD 90,000 - 130,000; Full time

Benefits offered by this job

Databricks platform experience

Job summary

KLANIK is seeking a Data Engineer to design, build, and maintain a scalable data platform supporting analytics and data science use cases in Miami. You will focus on Databricks-based pipelines, data quality, and modern DevOps practices, collaborating with BI, Analytics, and business stakeholders.

You will design ETL/ELT pipelines, evolve the Medallion architecture, and mentor team members while contributing to platform administration and documentation.

Qualifications

• Bachelor's degree in Computer Science or related field; Master’s preferred.
• 3+ years of experience as a Data Engineer.
• 2+ years building Databricks pipelines.
• Strong SQL and Python / PySpark / SparkSQL skills.
• 2+ years of dbt experience and Terraform usage.

Responsibilities

• Design and optimize ETL/ELT data pipelines on Databricks and AWS.
• Maintain and evolve the Medallion architecture.
• Build reusable frameworks for data ingestion, transformation and validation.
• Develop data models, schemas and datasets for analytics and visualization.
• Implement data quality checks and anomaly detection.
• Apply DevOps and CI/CD practices, leveraging Terraform.
• Collaborate with cross-functional teams and support data infrastructure needs.
• Document pipelines, data models and technical processes.

Skills

SQL

Python/PySpark

SparkSQL

dbt

Terraform

Git CI/CD

Big data modeling

Databricks

Data pipelines

Education

Bachelor's degree in Computer Science

Master's degree preferred

Tools

Databricks

Snowflake

BigQuery

Job description

KLANIK is seeking a Data Engineer to design, build, and maintain a scalable data platform supporting analytics and data science use cases in Miami. You will focus on Databricks-based pipelines, data quality, and modern DevOps practices, collaborating with BI, Analytics, and business stakeholders.

You will design ETL/ELT pipelines, evolve the Medallion architecture, and mentor team members while contributing to platform administration and documentation.