Senior Data Engineer

CARE

. Design, develop, implement, and maintain scalable data pipelines and enterprise data solutions .

Posted 10/30/2026full-timeRemote • United StatesSenior💰 $120,000 - $160,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and implementing scalable data pipelines and enterprise data solutions using Databricks, SQL, and Azure. Proven ability to optimize data storage and processing while collaborating effectively with cross-functional teams.

Highest-signal resume keywords

Data EngineeringDatabricksSQLAzure Data FactoryPython

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data Pipeline DevelopmentData TransformationData IntegrationBatch ProcessingStreaming Data ProcessesData Architecture StandardsData Engineering Best PracticesAutomationCI/CD PipelinesOrchestration Tools

Soft Skills

Analytical SkillsProblem-SolvingCollaborationMentorshipQuality Assurance

Tools & Technologies

DatabricksDbtAzureAzure Data FactoryAirflow

Industry Keywords

Cloud Data EcosystemsData LakesData WarehousesStructured DataSemi-Structured Data

Tech Stack

Tools & technologies

AirflowAzureCloudPythonSQL

About the role

Key responsibilities & impact

Design, develop, implement, and maintain scalable data pipelines and enterprise data solutions
Ingest, transform, integrate, and deliver complex data from multiple sources
Develop and maintain architecture standards, reusable frameworks, and data engineering best practices
Build automated systems for data ingestion, transformation, and orchestration using cloud-native and open-source tools
Optimize data storage and processing in data lakes and cloud data warehouses using Azure and Databricks
Develop and monitor batch and streaming data processes for accuracy, consistency, and timeliness
Maintain documentation and lineage tracking across datasets and pipelines
Collaborate with analysts, data scientists, software engineers, business stakeholders, contractors, and third-party vendors
Review and refine team members’ work to ensure quality and performance standards
Provide technical mentorship to junior team members
Use Databricks, dbt, Azure Data Factory, and SQL to architect and deploy data engineering solutions
Integrate APIs, structured and unstructured data sources, and third-party systems into centralized data platforms
Evaluate and implement technologies that improve scalability, observability, and automation
Suggest improvements to infrastructure, processes, and automation to improve efficiency, reduce costs, and enhance performance

Requirements

What you’ll need

Bachelor’s or master’s degree in computer science, Information Systems, Engineering, or a related field
5+ years of experience in data engineering with a proven track record of building cloud-based, production-grade data pipelines
Strong expertise in Databricks, SQL, dbt, Python, and cloud data ecosystems such as Azure
Experience working with structured and semi-structured data from diverse domains
Familiarity with CI/CD pipelines, orchestration tools (e.g., Airflow, Azure Data Factory), and modern software engineering practices
Strong analytical and problem-solving skills, with the ability to address complex data challenges and drive toward scalable solutions
Ability to use keyboards and other computer equipment
Must be able to work remotely within the United States
Care Access is unable to sponsor work visas at this time

Benefits

Comp & perks

Paid Time Off (PTO) and Company Paid Holidays
100% Employer paid medical, dental, and vision insurance plan options
Health Savings Account and Flexible Spending Accounts
Bi-weekly HSA employer contribution
Company paid Short-Term Disability and Long-Term Disability
401(k) Retirement Plan, with Company Match