Data Engineer - Azure (Contract) at Auxo Solutions LLC

Jacksonville, Florida, United States -

Full Time

Start Date

Immediate

Expiry Date

13 Mar, 26

Salary

0.0

Posted On

13 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Azure, ETL Processes, Data Factory, Databricks, SQL, Python, Data Modeling, Schema Optimization, Infrastructure-as-Code, CI/CD Pipelines, Data Warehousing, Agile, Waterfall, Data Quality, Technical Guidance

Industry

Software Development

Description

About the role As a Data Engineer (Contract to hire) with Auxo Solutions, your responsibilities encompass the implementation of strategies for modernizing/remediating platforms by leveraging modern tools and integrating new data platform capabilities. Your role involves close collaboration with diverse teams, including UX designers, application engineers, technical project managers, and application developers. The primary objective is to guarantee the delivery of top-tier applications that consistently exceed customer expectations. What you'll do Collaborate with project team(s) to implement new technologies, design ETL processes, and administer databases. Design, develop, build, and own robust and high-performance data pipelines/APIs using Azure Data Factory/Databricks. Collaborate with the Data Engineering team to assemble large, complex data sets which meet functional and non-functional business requirements. Architect infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Data Build Tool (dbt) and Azure technologies. Create and manage processes that support data transformation, data structures, metadata, dependency and workload management. Define and document cloud solution architecture(s) including technical designs and diagrams. Generate and document unit test scripts. Take a proactive approach in the overall ownership of data quality, overseeing architectural decisions and evaluating system implementations. Act as the escalation point of contact for Data Engineering issues. Propose and present solution recommendations, offering technical guidance to project teams. Provide innovative solutions to address complex business problems and challenges. Qualifications Bachelors’ Degree in Computer Science or a related field, along with relevant Tech/Software Certifications (Azure Cloud Certifications strongly preferred). At least 5 years’ of experience working in Data Engineering, with strong proficiency in Azure services such as: Data Factory, Synapse Analytics, Data Lake, Azure SQL, and hybrid Azure Stack environments. Experience deploying Azure Infrastructure-as-code (IaC) and building CI/CD pipelines. Strong skills in ETL workflows, data modeling, and schema optimization. Strong command of Python, SQL, and scripting for automation along with data warehousing and ETL best practices. Insurtech and/or Insurance experience is a plus. Ability to navigate an Agile/Waterfall software development project for external clients with very little oversight. Other Info This is a contract position expected to last about 6 months with a high likelihood of converting to FTE either with Auxo or directly with one of our end clients. The role requires occasional travel to client sites in the Jacksonville FL area (once a month). The interview process includes several coding exams, to be completed without the use of AI. The selected candidate will be subject to background checks, including employer, education, and location verifications. The candidate may also be asked to verify identification in person. Auxo team members must be available to work 8:30am - 5:30pm EDT on weekdays. No agencies please - no C2C - please do not reach out to us asking if we work with agencies.

Responsibilities

The Data Engineer will collaborate with project teams to implement new technologies and design ETL processes while ensuring the delivery of high-performance data pipelines. They will also oversee data quality and act as the escalation point for Data Engineering issues.