TL;DR

Databricks Data Engineer: Designing and building scalable data pipelines on the Databricks Lakehouse platform with an accent on ETL/ELT processes and Delta Lake table optimization. Focus on optimizing Spark jobs for performance, scalability, and cost efficiency.

Location: Remote

Company

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What you will do

Design and develop ETL/ELT pipelines using Databricks (PySpark, Spark SQL).
Build and optimize Delta Lake tables for batch and streaming workloads.
Implement data quality, validation, and monitoring frameworks.
Collaborate with data analysts, data scientists, and business stakeholders.
Work with cloud services on AWS / Azure / GCP.

Requirements

3–6 years of experience in Data Engineering.
Databricks Certified Professional – Data Engineer (Mandatory)
Strong hands-on experience with Databricks.
Expertise in Apache Spark, PySpark, Spark SQL.
Experience with Delta Lake and Lakehouse architecture.
Experience with at least one cloud platform (AWS, Azure, or GCP).

Nice to have

Experience with streaming technologies (Kafka, Event Hubs, Kinesis).
Familiarity with orchestration tools (Airflow, Azure Data Factory, AWS Glue).
CI/CD experience for data pipelines.
Exposure to BI or ML workloads on Databricks.