Data Engineer - Remote w2

Nexiva Inc; New York (NY); Remote; USD 120,000 - 160,000; Full time

Job summary

Nexiva Inc. is seeking a Data Engineer to design, develop, and maintain scalable data pipelines for enterprise analytics. This role partners with data scientists, analysts, and business teams to deliver high-quality data for reporting, analytics, and ML initiatives.

The position requires 5+ years in data engineering, strong SQL, Python, Spark, and hands-on cloud experience (Azure/AWS/GCP). Expect agile collaboration and remote-friendly arrangements with periodic onsite as needed.

Qualifications

• Strong SQL and relational database experience.
• 5+ years in Data Engineering or related roles.
• Hands-on ETL/ELT development experience.
• Experience with cloud data platforms (Azure/AWS/GCP).
• Python, Spark or comparable data processing techs.
• Knowledge of data warehousing concepts and governance.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines.
• Build data integration across diverse sources and data models.
• Develop data warehouses and data lake environments.
• Ensure data quality, governance, and security standards.
• Collaborate with stakeholders to translate requirements into data solutions.
• Monitor data workflows and optimize performance; document lineage.

Skills

SQL

ETL/ELT development

Python

Spark

Cloud platforms

Data modeling

Data governance

Communication

Education

Bachelor's degree in CS/IS/Engineering

Tools

Azure Databricks

Databricks

Azure Synapse/Snowflake

Job description

Title: Data Engineer
Location: REMOTE -- Still need candidates in these cities but they should only expect to go onsite 2-3x per month
Dallas/Frisco, Tampa/ FTL, NYC, Louisville, Chicago, ATL, Boston, Nashville, Charlotte (expect to go onsite 2-3x per month)
Duration: 12+ Months Contract to hire
Interview Mode: Video

Job Description

Position Overview

They need AI experience along with all the must haves

Client is seeking a Data Engineer to support enterprise data and analytics initiatives by designing, developing, and maintaining scalable data pipelines and solutions. This individual will work closely with business stakeholders, data analysts, data scientists, and technology teams to ensure high-quality, accessible data that supports reporting, analytics, and operational decision-making across the organization.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines.
• Build and optimize data integration processes from multiple internal and external sources.
• Develop and support data models, data warehouses, and data lake environments.
• Ensure data quality, integrity, consistency, and governance standards are met.
• Collaborate with business and technical teams to translate requirements into data solutions.
• Monitor and troubleshoot data workflows and production issues.
• Optimize database performance, query efficiency, and data processing jobs.
• Support analytics, reporting, machine learning, and business intelligence initiatives.
• Create and maintain technical documentation and data lineage processes.
• Participate in Agile development activities, including sprint planning and backlog grooming.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.
• 5+ years of experience in Data Engineering or related data development roles.
• Strong experience with SQL and relational databases.
• Hands-on experience developing ETL/ELT processes.
• Experience with cloud data platforms such as Azure, AWS, or Google Cloud.
• Proficiency with Python, Spark, or other data processing technologies.
• Experience working with large-scale structured and unstructured datasets.
• Understanding of data warehousing concepts and dimensional modeling.
• Knowledge of data governance, security, and compliance best practices.
• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

• Healthcare or payer industry experience.
• Experience supporting Medicare, Medicaid, or healthcare analytics initiatives.
• Familiarity with Azure Data Factory, Databricks, Synapse, Snowflake, Hadoop, or similar technologies.
• Experience with Power BI, Tableau, or other BI/reporting tools.
• Exposure to machine learning and advanced analytics environments.
• Experience working in highly regulated healthcare environments.

Notes

• Designs, builds, and maintains scalable data processing solutions and data pipelines
• Works with structured and unstructured data to support analytics and business insights
• Uses cloud-native technologies and engineering best practices
• Specifically mentions:
  • Azure Databricks
  • Large-scale data pipeline development and optimization