Databricks Engineer

Openkyber, LLC; United States; Remote; USD 110,000 - 170,000; Full time

Job summary

Openkyber is seeking a hands-on Data Engineer to design, build, and maintain scalable ETL/ELT pipelines using DBT and Databricks, in a fully remote role.

You will optimize SQL queries, work with cloud data platforms (AWS/Azure/GCP), and collaborate with analysts and stakeholders to enable trusted analytics.

The role involves data modeling, data quality, governance, and CI/CD practices to ensure production reliability.

Qualifications

• Experience as a Data Engineer with DBT for transformation workflows.
• Strong SQL with deep understanding of joins, window functions, CTEs, and performance tuning.
• Hands-on Databricks experience (Spark, Delta Lake, Notebooks).
• Experience with at least one cloud data platform: AWS Redshift, Azure Synapse, or Google BigQuery.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines using DBT and Databricks.
• Develop, optimize, and troubleshoot complex SQL queries for data transformations, validations, and reporting.
• Collaborate with data analysts, data scientists, and business stakeholders to understand data needs.
• Implement data quality and data governance best practices in pipelines.
• Work with structured and semi-structured data from multiple sources (APIs, flat files, cloud storage).
• Build and maintain data models (star/snowflake schemas) to support analytics and BI tools.
• Monitor pipeline performance and troubleshoot issues in production environments.
• Maintain version control, testing, and CI/CD for DBT projects using Git and DevOps pipelines.

Skills

Data engineering

SQL proficiency

Git and version control

Python or PySpark

Stakeholder communication

Tools

DBT

Databricks

Airflow

Git

CI/CD

Python

PySpark

Cloud platforms

BigQuery

Redshift

Delta Lake

Notebooks

Spark

Job description

Job Title: Data Engineer DBT, Databricks & SQL Expert Location: Remote

Key Responsibilities

• Design, build, and maintain scalable and efficient ETL/ELT pipelines using DBT and Databr icks .
• Develop, optimize, and troubleshoot complex SQL queries for data transformations, validations, and reporting.
• Collaborate with data analysts, data scientists, and business stakeholders to understand data needs.
• Implement data quality and dat a governance best practices in pipelines.
• Work with structured and semi-structured data from multiple sources (e.g., APIs, flat files, cloud storage).
• Build and maintain data models (star/ snowflake schemas) to support analytics and BI tools.
• Monitor pipeline performance and troubleshoot issues in production environments.
• Maintain version control, testing, and CI/CD for DBT projects using Git and DevOps pipelines.

Required Skills & Experience

• experience as a Data Engineer Strong experience with DBT (Cloud or Core) for transformation workflows.
• Proficiency in SQL deep understanding of joins, window functions, CTEs, and performance tuning.
• Hands-on experience with Databricks (Spark, Delta Lake, Notebooks).
• Experience with at least one cloud data platform : AWS (Redshift), Azure (Synapse), or Google Cloud Platform (BigQuery).
• Familiarity with data lake and lakehouse architecture.
• Experience with Git and version control in data projects.
• Knowledge of orchestration tools like Airflow, Azure Data Factory, or dbt Cloud scheduler.
• Comfortable with Python or PySpark for data manipulation (bonus).