Senior Cloud Data Engineer

Arbitration Forums, Inc.
Tampa, United States of America
10 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Remote
Tampa, United States of America

Tech stack

Microsoft Access
Java
Artificial Intelligence
Amazon Web Services (AWS)
Azure
Big Data
Cloud Database
Code Review
Information Systems
Computer Engineering
Continuous Integration
Data as a Services
Information Engineering
Data Governance
ETL
Data Masking
Data Security
Data Warehousing
Database Queries
DevOps
Github
Monitoring of Systems
Information Technology Operations
Python
Power BI
Cloud Services
Tableau
Talend
Google Cloud Platform
Azure
Snowflake
Gitlab
Information Technology
Machine Learning Operations
Data Pipelines
Databricks
Programming Languages

Job description

This role at Arbitration Forums is as unique as it is rewarding because of the AF IPAAL Values (Integrity, Passion, Accountability, Achievement, Leadership) and TRI Model (Trust, Respect, Inclusion).

The Senior Cloud Data Engineer will be responsible for designing, developing, and implementing robust, scalable, and secure data pipelines for modern cloud platforms to support analytics and AI/ML needs at Arbitration Forums, Inc. This role will streamline data acquisition from different data sources and set up processes to ensure data quality and data security.

DEPARTMENTAL EXPECTATION OF EMPLOYEE

  • Adheres to AF Policy and Procedures and the AF IPAAL Values and TRI Model
  • Acts as a role model within and outside AF.
  • Performs duties as workload necessitates.
  • Maintains a positive and respectful attitude.
  • Communicates regularly with the departmental leader about department issues.
  • Demonstrates flexible and efficient time management and ability to prioritize workload.
  • Consistently reports to work on time, prepared to perform duties of the position.
  • Meets Department productivity standards., Data Engineering & Pipeline Development:
  • Design, develop, and implement robust, scalable, and secure data pipelines in a cloud environment.
  • Build and manage ETL/ELT processes to efficiently move and transform large datasets from multiple data sources.
  • Implement secure data access, encryption, and data masking policies.
  • Develop automated processes to validate data quality and data accuracy.
  • Document and maintain data workflows and diagrams.
  • Work with data scientists and AI specialists to automate model deployment lifecycles (MLOps).

Data pipeline/warehouse management

  • Configure and maintain cloud-based data warehousing solutions.
  • Optimize data warehouse storage strategies to support analytics and data science needs.
  • Set up monitoring tools and alerts to maintain data warehouse availability and reliability.
  • Troubleshoot, profile, and optimize data pipelines for performance issues to minimize latency.

Collaboration

  • Work closely with data architects, data analysts and data scientists to understand their data needs and translate them into technical designs.
  • Mentor and guide junior data engineers, perform code reviews, and establish best practices for could data engineering.
  • Collaborate with DevOps and ITOps to implement CI/CD pipelines and robust DR strategies.

Requirements

Do you have experience in Talend?, Do you have a Bachelor's degree?, * Bachelor's degree in computer science, Computer Engineering, Information Systems, or a related field.

  • 7+ years of experience in data engineering with a focus on cloud data engineering.

Technical Skills:

  • Profound understanding of major cloud platforms (AWS, GCP, Azure) and major cloud data platforms like Snowflake and Databricks.
  • Hands-on experience with data services offered by cloud platforms.
  • Expertise in programming languages such as Python, Java, or Scala with strong SQL skills.
  • Experience with ETL/ELT tools like Talend, DBT, Azure Data Factory, etc.
  • Experience with CI/CD tools like GitLab/GitHub.
  • Strong knowledge of data governance, data security, and compliance practices.
  • Experience supporting data science and machine learning operations.
  • Familiarity with data visualization and reporting tools (e.g., Power BI, Tableau).

Soft Skills:

  • Excellent analytical and problem-solving abilities.
  • Strong communication and interpersonal skills to collaborate with cross-functional teams.
  • Auto Insurance claims industry experience preferred.

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