Data Engineer (4168-1) Columbus, OH

ESR Healthcare; Columbus (OH); On-site; USD 80,000 - 110,000; Full time

Job summary

Join a forward-thinking company as a Data Engineer, where you will leverage your skills in Databricks and Python to build robust ETL pipelines. This role offers an exciting opportunity to work with cutting-edge technologies like Azure Data Lake Storage and Docker, enabling you to drive data-driven decisions and enhance operational efficiency. As a key player in the data engineering team, you will contribute to automating processes and ensuring data integrity, making a significant impact on the organization’s analytics capabilities. If you are passionate about data and eager to innovate, this position is perfect for you.

Qualifications

• 10+ years of experience in data engineering with a focus on ETL processes.
• Strong expertise in Databricks and Azure data solutions.

Responsibilities

• Build and maintain ETL pipelines for data processing and integration.
• Automate data quality checks and optimize data workflows.

Skills

Databricks

ETL pipelines

Docker

Python

Apache Airflow

PySpark

Education

Bachelor's degree

Tools

Azure Data Lake Storage

Azure Data Factory

Job description

Data Engineer (4168-1) Columbus, OH

Databricks, ETL pipelines, Docker for containerization, utilizing REST API in Python, Python

Experience level: Mid-senior
Experience required: 10 Years
Education level: Bachelor’s degree
Job function: Information Technology
Industry: Information Technology and Services
Pay rate: View hourly payrate
Total position: 1
Relocation assistance: No
Visa sponsorship eligibility: No

Job Summary

• Strong experience in Databricks
• Expertise in implementing batch and real-time data processing solutions using Azure Data Lake Storage, Azure Data Factory, and Databricks
• Experience in building ETL pipelines for ingesting, transforming, and loading data from multiple sources into cloud data warehouses
• Proficient in Docker for containerization, utilizing REST API in Python for system integration, and applying containerization to improve deployment efficiency and scalability
• Experience in data extraction, acquisition, transformation, manipulation, performance tuning, and data analysis
• Skilled in using Python libraries to build efficient data processing workflows and streamline ETL operations across large datasets and distributed systems
• Expertise in automating data quality checks, reducing data errors by 40%, and ensuring reliable reporting and analytics with data marts
• Proficient in data orchestration and automation tools such as Apache Airflow, Python, and PySpark for end-to-end ETL workflows
• Experience in deployment activities