Pay Rate : $open on w2 / c2c
Make sure to apply with all the requested information, as laid out in the job overview below.
Role : Data Engineer
Client : Retail (Through PV)
Position : Contract
Positions : 6
Duration : 24+ months
Work : Remote for now
Interview : Video
Client Location : Cincinnati, OH
Experience Required : 8-12 years
SR. DATA ENGINEER (4 POSITIONS)
Top 3 skills needed : Azure Databricks, Spark / PySpark, SQL
The ideal candidate for the Data Engineer role will possess strong technical proficiency in a variety of tools and technologies relevant to data engineering in Azure cloud environments.
This includes demonstrated expertise in Azure Databricks for building and optimizing data pipelines, as well as experience with Azure Synapse Analytics for data warehousing and analytics.
Proficiency in SQL is essential for querying and manipulating data within these platforms, along with programming skills in Python and PySpark for data processing and transformation tasks.
Additionally, the candidate should have experience working with distributed computing frameworks and familiarity with cloud-based storage solutions such as Azure Blob Storage and Azure Data Lake Storage.
Knowledge of data modeling, ETL processes, and data security best practices is also crucial for designing and implementing scalable and reliable data solutions.
The ability to troubleshoot and optimize data processing workflows, along with strong problem-solving skills, is essential for ensuring the performance and efficiency of data pipelines in high-throughput environments.
DATA QUALITY ENGINEER (2 POSITIONS)
Top skills needed : testing, SQL, Azure Databricks, and Spark / PySpark
We are seeking a skilled Data Quality Engineer to join our team and play a critical role in ensuring the reliability, accuracy, and consistency of data within our warehouse and manufacturing data platform in the Client supply chain space.
While the title may suggest a focus on quality assurance, this role requires a blend of data engineering and testing expertise.
The Data Quality Engineer will be responsible for implementing robust test frameworks, writing automation test cases, and collaborating closely with data engineers to validate and verify the functionality of data pipelines and processes.
This is a key role in maintaining the integrity of our data platform and driving continuous improvement in data quality standards.
Technical Skills
- Proficiency in data engineering technologies such as Azure Databricks, Synapse Analytics, and SQL Hyperscale.
- Strong programming skills in Python and PySpark for developing automation test scripts.
- Experience with building and implementing test frameworks for data-centric applications in Azure cloud environments.
- Knowledge of data quality assurance methodologies and best practices.
- Familiarity with version control systems and CI / CD pipelines for automated testing and deployment.
- Understanding of data modeling, ETL processes, and data warehousing concepts.
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