Databricks Engineer

Conquest Tech Solutions Inc; Arizona; On-site; USD 140,000 - 190,000; Full time

Job summary

Conquest Tech Solutions Inc in the United States is seeking a Databricks Engineer to lead the design, implementation, and optimization of scalable cloud-based data platforms. This role requires deep expertise in Lakehouse architecture, Databricks, Apache Spark, and Delta Lake, with a track record of delivering end-to-end enterprise data solutions.

You will design end-to-end pipelines, build real-time and batch processing, implement data quality and governance, and drive CI/CD automation.

Qualifications

• End-to-end data platform design and implementation experience.
• Hands-on expertise with Spark-based batch and streaming pipelines.
• Strong knowledge of data modeling and warehouse strategies.

Responsibilities

• Design and deliver end-to-end data engineering pipelines, including batch and real-time streaming.
• Lead implementation of cloud-based data lakehouse platforms.
• Develop ETL/ELT pipelines using PySpark, Scala, and SQL.
• Implement data quality frameworks and governance standards.
• Manage Unity Catalog and fine-grained security.
• Drive CI/CD automation and DevOps practices for pipelines.
• Collaborate with stakeholders to translate business requirements into scalable solutions.

Skills

Databricks

Apache Spark

Delta Lake

Lakehouse architecture

PySpark

Scala

SQL

Python

CI/CD

DevOps

Tools

Delta Live Tables

Autoloader

Structured Streaming

Databricks Workflows

Airflow

Unity Catalog

Job description

Role / Skills Databricks Engineer

Location Pheonix Day 1 Onsite min 3 days a week.

JD

Databricks Engineer

Role Overview

We are seeking a highly skilled Databricks Engineer to lead the design, implementation, and optimization of scalable cloud-based data platforms. This role requires deep expertise in Lakehouse architecture, Databricks, Apache Spark, and Delta Lake, along with proven experience delivering end-to-end enterprise data engineering solutions.

Key Responsibilities

• Design and deliver end-to-end data engineering pipelines, including batch and real-time streaming solutions.
• Lead implementation of:
• Cloud-based data lakehouse platforms integrating diverse data sources.
• Real-time data processing pipelines for operational and analytical use cases.
• Develop scalable ETL/ELT pipelines using PySpark, Scala, and SQL.
• Implement advanced data modeling solutions including 3NF, dimensional modeling, and enterprise data warehousing strategies.
• Design and build incremental data loading frameworks and metadata-driven ingestion pipelines.
• Establish data quality frameworks and governance standards.
• Implement and manage Unity Catalog, including fine-grained security and access controls.
• Leverage Databricks components such as:
• Delta Live Tables
• Autoloader
• Structured Streaming
• Databricks Workflows
• Integration with orchestration tools (e.g., Apache Airflow)
• Drive CI/CD automation, deployment strategies, and DevOps best practices.
• Optimize performance of pipelines, Spark jobs, and compute resources.
• Provide architectural guidance and technical leadership across cross-functional teams.
• Engage with stakeholders and clients to translate business requirements into scalable technical solutions.

Deep expertise in:

• Databricks and cloud-native storage/compute platforms
• Apache Spark (batch & streaming)
• Delta Lake & Lakehouse architecture
• Distributed data processing systems
• Strong hands-on programming skills in Python, PySpark, Scala, and SQL.