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Principal Cloud Data Engineer

Relativity ODA
Full-time
On-site
Illinois, United States
$210,000 - $314,000 USD yearly

Posting Type

Hybrid

Job Overview

We are seeking an experienced and innovative Cloud Data Engineer to join our team. The Cloud Data Engineer will design, implement, and manage cloud-based data architecture solutions, ensuring they are scalable, reliable, and secure. This role involves collaborating with various stakeholders, including product managers, engineers, and business leaders, to align cloud data strategies with organizational goals.

Job Description and Requirements

Data Model and Structure Definition: 

  • Design and develop conceptual, logical, and physical data models for both structured and unstructured data. 

  • Collaborate with stakeholders to understand data requirements and translate them into effective data models. 

  • Ensure data models are aligned with business goals and effectively support transactional, analytical and operational needs. 

Data Technologies: 

  • Design and develop data technology strategy and associated roadmaps. 

  • Utilize cloud-native technologies to implement and manage data models. 

  • Work with data tools and platforms (e.g., Hadoop, Spark, Kafka) to handle large volumes of data. 

  • Optimize data storage, retrieval, and processing in a cloud environment. 

  

Data Integration and ETL: 

  • Design and implement ETL processes to integrate data from various sources into the data lakes 

  • Ensure data quality, consistency, and integrity throughout the data lifecycle. 

  • Develop and maintain documentation for data models and ETL processes. 

  

Performance Tuning and Optimization: 

  • Analyze and optimize data models to improve performance and scalability. 

  • Monitor and troubleshoot data-related issues to ensure optimal system performance. 

  • Implement best practices for data management and governance, including defining best practices around ownership, linage, security, and quality. 

  

Collaboration and Communication: 

  • Work closely with engineers, data scientists, and business analysts to deliver data solutions, oftentimes working directly in code alongside them 

  • Communicate complex data concepts and solutions to both technical and non-technical stakeholders, including executives and senior leadership 

  • Participate in data architecture reviews and provide recommendations for improvements. 

  • Partner with senior leadership to ensure strategic plans are being met. 

  • Clear roadblocks by building consensus across the organization via a variety of influencing techniques. 

 

Minimum Requirements 

  • Atleast 10 years of related work experience  

  • Proficiency in cloud services and tools (e.g., Amazon S3, Azure Data Lake, Google BigQuery). 

  • Expert understanding of data modeling, database design, and delta lake concepts. 

  • Expert knowledge of data integration and ETL tools (e.g., dbt, Apache NiFi, Talend, Informatica, Azure Data Factory, Prefect). 

  • Strong familiarity with big data technologies (e.g., Hadoop, Spark, Kafka, Delta Lake, Iceberg, Arrow, Data Fusion). 

  • Strong familiarity with data governance tooling (e.g. Alation, Collibra, BigID, Purview, Monte Carlo) 

  • Strong programming skills in languages such as Python, Java, Scala, or Rust. 

  • Excellent problem-solving and analytical skills. 

  • Strong communication and interpersonal skills. 

  • Ability to work collaboratively in a team environment. 

  • Project management and organizational skills. 

Relativity is committed to competitive, fair, and equitable compensation practices.

This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives.

The expected salary range for this role is between following values:

$210,000 and $314,000

The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position.