Data Engineer

Title : Data Engineer

Location : Cincinnati OH (3 days on-site required)

Duration : 1 Year Contract (potential for conversion / extension)

The team is seeking a Data Engineer experienced in implementing modern data solutions in Azure with strong hands-on skills in Databricks Spark Python and cloud-based DataOps practices. The Data Engineer will analyze design and develop data products pipelines and information architecture deliverables focusing on data as an enterprise asset. This role also supports cloud infrastructure automation and CI / CD using Terraform GitHub and GitHub Actions to deliver scalable reliable and secure data solutions.

Key Responsibilities

Analyze design and develop enterprise data solutions with a focus on Azure Databricks Spark Python and SQL

Develop optimize and maintain Spark / PySpark data pipelines including managing performance issues such as data skew partitioning caching and shuffle optimization

Build and support Delta Lake tables and data models for analytical and operational use cases

Apply reusable design patterns data standards and architecture guidelines across the enterprise including collaboration with end client when needed

Use Terraform to provision and manage cloud and Databricks resources supporting Infrastructure as Code (IaC) practices

Implement and maintain CI / CD workflows using GitHub and GitHub Actions for source control testing and pipeline deployment

Manage Git-based workflows for Databricks notebooks jobs and data engineering artifacts

Troubleshoot failures and improve reliability across Databricks jobs clusters and data pipelines

Apply cloud computing skills to deploy fixes upgrades and enhancements in Azure environments

Work closely with engineering teams to enhance tools systems development processes and data security

Participate in the development and communication of data strategy standards and roadmaps

Draft architectural diagrams interface specifications and other design documents

Promote the reuse of data assets and contribute to enterprise data catalog practices

Deliver timely and effective support and communication to stakeholders and end users

Mentor team members on data engineering principles best practices and emerging technologies

Requirements

7 years of experience as a Data Engineer

Hands-on experience with Azure Databricks Spark and Python

Experience with Delta Live Tables (DLT) and Databricks SQL

Strong SQL and database background

Experience with Azure Functions messaging services or orchestration tools

Familiarity with data governance lineage or cataloging tools (e.g. Purview Unity Catalog)

Experience monitoring and optimizing Databricks clusters or workflows

Experience working with Azure cloud data services and understanding how they integrate with Databricks and enterprise data platforms

Experience with Terraform for cloud infrastructure provisioning

Experience with GitHub and GitHub Actions for version control and CI / CD automation

Strong understanding of distributed computing concepts (partitions joins shuffles cluster behavior)

Familiarity with SDLC and modern engineering practices

Ability to balance multiple priorities work independently and stay organized

Key Skills

Apache Hive,S3,Hadoop,Redshift,Spark,AWS,Apache Pig,NoSQL,Big Data,Data Warehouse,Kafka,Scala

Employment Type : Full Time

Experience : years

Vacancy : 1