Staff Data Engineer

DAT; United States; Hybrid; USD 130,000 - 190,000; Full time

Benefits offered by this job

Remote/hybrid flexibility

Wellness allowance

Parental leave

Career development paths

Stock purchase program

Immediate 401(k) matching

Mental health support

Life insurance

20 days PTO + 10 holidays

Job summary

DAT is seeking a senior data platform engineer to lead the evolution of a scalable data architecture in a hybrid work environment. You will partner with senior IT leaders to drive data initiatives, enforce governance, and shape platform strategy using dbt, Airflow, Snowflake, Kafka, and AWS.

You will design and implement advanced data models, lead enterprise-scale infrastructure, and promote a culture of engineering excellence with strong focus on security, CI/CD, and performance.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or related technical discipline
• 7+ years of relevant engineering experience building and operating large-scale distributed systems
• Proven ability to design scalable, reliable data platforms and lead strategic data initiatives
• Strong communication skills and ability to collaborate with senior leadership and IT stakeholders
• Experience with dbt, Snowflake, Kafka and cloud-based services (AWS) is preferred

Responsibilities

• Lead the design and evolution of a modern data platform architecture for scalability, availability, and performance
• Apply advanced architectural patterns (Event Driven, CQRS, event sourcing, Saga) to solve complex data challenges
• Develop, document, and enforce standard methods and processes across the technology stack (dbt, Airflow, Snowflake, Kafka)
• Collaborate with senior leadership on strategic data projects and provide technical thought leadership
• Architect and manage enterprise-scale data platforms with best practices for security, privacy, monitoring, CI/CD
• Implement data modeling strategies (Kimball, Inmon, Data Vault) and drive toward Data Mesh concepts
• Provide solutions to complex business problems enabling insights for better decision-making
• Set and enforce best practices for the software development lifecycle, including coding standards, reviews, source control, and testing
• Foster a culture of learning and excellence within the engineering organization
• Leverage data to influence priorities and outcomes across the organization
• Lead change management to optimize platform and processes

Skills

Event Driven

CQRS

Event Sourcing

Saga patterns

Data modeling

Distributed systems

Security & privacy

CI/CD

Leadership

Data Mesh

Education

Bachelor's degree in CS/CE or related

Tools

dbt

Apache Airflow

Snowflake

Kafka

AWS

Terraform

Tableau

MySQL

Oracle

Job description

• Platform Evolution: Lead the design and evolution of our modern data platform architecture, ensuring it remains scalable, available, and performant
• Pattern Implementation: Apply in-depth knowledge of advanced architectural patterns- such as Event Driven, CQRS, event sourcing, and Saga patterns to solve complex data challenges
• Technical Governance: Develop, document, and communicate standard methods and processes to be utilized within our technology stack, including dbt, Airflow, Snowflake, Kafka, and traditional ETL
• Strategic Collaboration: Act as a key partner to senior leadership on strategic data projects and build strong working relationships with other IT leaders by providing technical acumen and thought leadership
• Enterprise-Scale Infrastructure: Architect and manage enterprise-scale data platforms while setting best practices for development teams, including security, privacy, monitoring & alerting, and CI/CD
• Advanced Data Modeling: Implement sophisticated data modeling strategies, including Kimball, Inmon, or Data Vault, and drive the transition toward modern concepts like Data Mesh
• Complex Problem Solving: Provide solutions for complex business problems, enabling insights that can empower better decision-making across the organization
• Operational Excellence: Set and enforce best practices for the full software development and technology management life cycle, including coding standards, code reviews, source control management, and testing
• Culture of Excellence: Take an active role in fostering a culture of learning and excellence within the engineering organization
• Influence through Data: Leverage data to prioritize work and influence others across the organization
• Change Management: Proactively implement change and improvements when seeing opportunities to optimize the platform or processes
• Current Technologies Being Used Today:
• Data Warehouse: Snowflake, Oracle, MySQL
• Transformation: dbt (data build tool)
• Orchestration: Apache Airflow
• Programming: Python, SQL
• Streaming: Kafka
• Cloud: AWS (S3, EMR, Glue)
• Infrastructure: Terraform

Benefits

• Remote/hybrid flexibility
• Wellness allowance
• Parental leave
• Career development paths
• Stock purchase program
• Immediate 401(k) matching
• Mental health support
• FSA/HSA optionsLife insurance
• 20 days PTO from day one, plus 10 paid holidays annually
• Leadership training, mentorship programs, education reimbursement & industry certifications
• Performance bonuses & annual merit increases
• Premium health coverage, plus dental & vision

Education: Bachelor's degree in Computer Science, Computer Engineering, or a related technical discipline

Experience: 7+ years of relevant professional engineering experience, with a proven track record of building and operating large-scale distributed systems

Communication: Excellent verbal and written communication skills with an interest in continuous learning and improvement

Data Engineering: Strong data engineering background working with dbt, Snowflake, Kafka, and cloud-based services (AWS S3, EMR, Glue)

Infrastructure & Tooling: Hands-on experience with Terraform, Airflow, Tableau, MySQL, and Oracle

Software Engineering: Deep knowledge of professional software engineering practices for the full technology management life cycle; experience with Agile is preferred