Sr. Engineer - DataOps

Carmax; Richmond (VA); Hybrid; USD 120,000 - 160,000; Full time

Job summary

A leading company in the automotive industry seeks a Senior DataOps Engineer to enhance Data & Analytics efficiency. The role includes developing cloud-based data solutions using advanced skills in Python, SQL, Azure, and Databricks, while collaborating for continuous improvement across teams.

Qualifications

• 5+ years of experience as a DataOps Engineer.
• Experience in Enterprise Data Lake/Warehouse (EDL/EDW) and Azure services.
• 5+ years leading the end-to-end design and development of scalable services.

Responsibilities

• Design, implement, and maintain cloud-based data pipelines and infrastructure solutions.
• Streamline development and operational processes via continuous integration.
• Mentor junior DevOps engineers and promote best practices in cloud technologies.

Skills

Python

SQL

Agile

DevOps

Automation

Education

Bachelor's/Master’s in computer science or equivalent area

Tools

Azure

Databricks

Snowflake

Job description

8116 - Midtown Office - 2220 W. Broad Street, Richmond, Virginia, 23220

CarMax, the way your career should be!

About this job

As a Senior DataOps Engineer, you will work closely with Data Engineering, Master Data Management, Data Governance and other Data & AI teams to ensure reliability and availability of Data & Analytics platforms, pipelines and business processes while developing tools to monitor and maintain the scalability and performance of cloud-based environments and operational processes. Your expertise in Site Reliability Engineering (SRE), automation, cloud technologies, and continuous integration of AI capabilities will help streamline our operations and enable faster, more reliable delivery of data-driven solutions. In a modern data ecosystem, it is important to have hands-on experience with Snowflake, Databricks, Azure Cloud Services, DevOps, CI/CD, Python, Shell scripting as well as strong fundamentals in different Platforms such as Enterprise Data Lake/Warehouse (EDL/EDW), and Azure Data Factory.

What you will do – Essential Responsibilities

• Design, implement, and maintain cloud-based data pipelines and infrastructure solutions for Data & Analytics platforms.
• Streamline development and operational processes via continuous integration, deployment, automated testing while leveraging Site Reliability Engineering (SRE) principles.
• Utilize Artificial Intelligence (AI) and Machine Learning (ML)tools to integrate intelligent automation into day-to-day data operations. Drive efficiency, reduce manual effort, and enhance the reliability and scalability of data pipelines by applying AI-powered solutions.
• Collaborate with cross-functional teams to identify opportunities leveraging AI/ML to continuously improve business processes and operational decision-making.
• Collaborate with partner teams to define and maintain procedures to ensure data quality, availability, and reliability.
• Automate manual tasks and build processes for SLA/SLI/SLO and error budget tracking.
• Troubleshoot and resolve issues related to cloud infrastructure, application performance, and data pipelines.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, and partnering with Data and Analytics teams for continuous review of ongoing opportunities.
• Stay current with DataOps industry best practices and adopt emerging technologies and solutions.
• Drive self service capabilities and ongoing automation initiatives.
• Perform root cause analysis for production issues and recommend improvements.
• Drive efficient resolution for system outages as well as performance and functional shortcomings. Engage in critical support situations and effectively, efficiently, and quickly drive successful resolution.
• Mentor junior DevOps engineers and promote best practices in cloud technologies, automation, and data operations.

Purpose of the role

The DataOps engineer will be a key contributor in driving automation, SRE maturity and efficiency in our Data & AI organization ensuring data is available and reliable throughout its lifecycle.

Qualifications and Requirements

Basic Qualifications

• 5+ years of experience as a DataOps Engineer.
• 3+ years of experience with reporting and visualization tools such as Tableau or Power BI.
• 3+ years of experience in Enterprise Data Lake/Warehouse (EDL/EDW), and expertise in Azure services.
• 5+ years leading the end-to-end design and development of scalable services to be consumed by the enterprise, including monitoring and production support.
• 5+ years developing, executing and automating operational processes.
• Advanced proficiency with Python, SQL, GitHub, Azure DevOps, Bicep templates, and PowerShell is required.
• 5+ years of DevOps experience with a clear understanding of related tools, structure, and processes working in an Agile/Scrum setting.
• Experience in cloud cost-savings plans, reviews, and reserved instances.
• Experience in DevOps and SRE practices, testing frameworks, Infrastructure as Code, and building CI/CD pipelines.
• Excellent communication skills with the ability to adapt to the audience
• Experience in a fast-paced, highly collaborative agile team within a Product-oriented organization.
• Effective problem-solving, analytical thinking, and a cloud-native and DevOps mindset.
• Strong documentation, communication, and presentation skills.
• Ability to positively influence team norms, culture, and technical vision.

Preferred Qualifications

• Bachelor's/Master’s in computer science or equivalent area
• Experience with cloud services such as Snowflake, Databricks, Azure Data Factory, Event Hub, Functions, Batch, Key Vault, and Log Analytics
• Strong experience with popular database programming languages such as SQL, PL/SQL, Stored Procedures
• Snowflake SnowPro, Azure, Databricks certifications
• Familiarity with microservices software architecture and Machine Learning experience is preferred.
• Working knowledge of ETL/ELT, CDC, Message-Oriented data movement, API design and stream data integration. Moderate experience with Big Data

Work Authorization: Applicants must be currently authorized to work in the United States on a full-time basis. Sponsorship will not be considered for this specific role.

Work Location and Arrangement: This role will be based out of one of the following locations and have a Hybrid work arrangement:
• Dallas, TX Technology Hub
• Richmond, VA Technology Innovation Center

About CarMax

CarMax disrupted the auto industry by delivering the honest, transparent and high-integrity experience customers want and deserve. This innovative thinkingaround the way cars are bought and soldhas helped us become the nation’s largest retailer of used cars, with over 200 locations nationwide.

Ouramazing team of more than 25,000 associates work together to deliver iconic customer experiences.Along the way,we help every associate grow their career and achieve their best, at work and in their community. We are recognized for our commitment to training and diversity and areone of the FORTUNE 100 Best Companies to Work For.

Our Commitment to Diversity and Inclusion:

CarMax is committed to bringing together people from different backgrounds and perspectives, providing employees with a safe, welcoming, and inclusive work environment.

CarMax is an equal opportunity employer, and all qualified candidates will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, genetic information, national origin, protected veteran status, disability status, or any other characteristic protected by law.

Upon an applicant's request, CarMax will consider reasonable accommodation to complete the CarMax Job Application.