Databricks Data Engineer

CloudIngest; Cincinnati (OH); On-site; USD 56,826 - 80,934; Full time

Job summary

CloudIngest is seeking a skilled Databricks Data Engineer in Cincinnati, Ohio, to design and optimize data pipelines on Azure. You'll work on enterprise-scale projects, closely collaborating with stakeholders to enhance data processing solutions.

Key responsibilities include developing ETL/ELT pipelines and ensuring data quality across all stages. Strong experience with Azure Databricks, PySpark, and SQL is mandatory for success in this role, which promises dynamic work in a thriving environment.

Qualifications

• Strong hands-on experience with Azure Databricks, PySpark, and SQL.
• Knowledge of data lakehouse architecture and Delta Lake.
• Experience with Azure ecosystem tools.

Responsibilities

• Develop and maintain ETL/ELT pipelines using Databricks, PySpark, and SQL.
• Integrate data from multiple sources into data lakes and warehouses.
• Collaborate with data scientists and analysts for advanced analytics.

Skills

Azure Databricks

PySpark

SQL

Data lakehouse architecture

ETL/ELT design

CI/CD pipelines

DevOps practices

Tools

Azure Data Lake

Azure Synapse

Azure Data Factory (ADF)

Azure Key Vault

Job description

Job Role/Title: - Databricks Data Engineer- (8+ Years experience)

Contract: Long Term Contract

Rate: $50/hr on W2 (Only W2) No C2C

Interview Mode: Candidate should go for F2F interview

NOTE: Need a very strong Azure Databricks, PySpark, and SQL

Job Summary

• We are seeking a skilled Databricks Data Engineer to design, build, and optimize data pipelines and analytics solutions on Azure Databricks for enterprise-scale projects.
• The role involves working closely with business stakeholders, data scientists, and architects to enable reliable, scalable, and secure data processing for IBM/Kroger initiatives.

Key Responsibilities

• Develop and maintain ETL/ELT pipelines using Databricks, PySpark, and SQL.
• Integrate data from multiple sources (structured, semi-structured, unstructured) into data lakes and warehouses.
• Optimize performance of large-scale data processing jobs.
• Collaborate with data scientists and analysts to enable advanced analytics and machine learning workloads.
• Ensure data quality, governance, and compliance across all pipelines.
• Support production environments, troubleshoot issues, and implement fixes.
• Document technical designs, workflows, and best practices.

Required Skill

Strong hands‑on experience with Azure Databricks, PySpark, and SQL.

• Knowledge of data lakehouse architecture and Delta Lake.
• Experience with Azure ecosystem (Data Lake, Synapse, ADF, Key Vault).
• Proficiency in ETL/ELT design, data modeling, and performance tuning.
• Familiarity with CI/CD pipelines and DevOps practices.
• Strong problem‑solving and communication skills.