Senior Data and Analytics Engineer

Velir offers a remote-first environment with a hybrid work model in New York, NY for US-based applicants. This role blends data engineering and analytics engineering to design, build, and optimize data pipelines, data models, and semantic layers, with Databricks as the primary platform. The position provides a competitive annual salary range of USD 160,000 to 175,000, along with excellent benefits.

Responsibilities

• Design and operate scalable data pipelines and ELT workflows, centered on Databricks
• Develop and maintain dbt models that are well documented, tested, and structured for long term maintainability
• Own data modeling decisions and methodology, defining entities, relationships, and grain in collaboration with analytics and business stakeholders
• Translate engagement-level vision into actionable tasks and deliverables
• Regularly deliver meaningful improvements to clients' data infrastructure and analytical capabilities
• Operate autonomously while providing technical guidance to less experienced engineers
• Collaborate with other data engineers, analytics engineers, data analysts, and clients on end-to-end data requirements
• Partner with clients and functional managers to plan data engineering and modeling needs for product or feature launches
• Create processes and documentation templates that help cross-functional teams solve common data problems
• Drive data solution improvements that impact the client experience or empower internal stakeholders to do their jobs effectively
• Identify, communicate, and solve important problems, coordinating with others on cross-cutting technical issues
• Architect and design data systems and transformation layers using patterns that support iterative delivery and future scaling
• Proactively address technical debt with careful evaluation of development costs
• Enhance predictability and maintain a regular cadence of deliverables
• Keep reliability, maintainability, and scalability of client systems top of mind
• Prioritize unowned or unglamorous work that enables the broader team to move faster

Requirements

• Proven experience as a Data Engineer, Analytics Engineer, or in a hybrid/generalist role focused on building data pipelines and transformation layers
• Strong programming skills in Python and SQL
• Hands-on expertise with Databricks, including Delta Lake, Unity Catalog, and Databricks workflows
• Proficiency with dbt for data transformation, testing, and documentation
• Demonstrated data modeling experience, including dimensional modeling, entity-relationship design, and semantic layer development
• Deep knowledge of data warehousing and ELT/ETL processes
• Familiarity with data integration and orchestration platforms such as Fivetran, Apache Airflow, and Azure Data Factory
• Experience with cloud platforms like AWS, Azure, or Google Cloud
• Experience with other cloud data warehouses such as Snowflake or Motherduck is a plus
• Experience with streaming solutions such as Spark Streaming or Kafka is desirable but not required
• Familiarity with MLOps techniques and platforms is a plus but not required
• Strong analytical and problem-solving skills
• Excellent communication and collaboration abilities
• Familiarity with coding assistants such as Claude Code, CoPilot, and Codex is a plus

Technologies

• Databricks
• Delta Lake
• Unity Catalog
• Databricks workflows
• dbt
• Python
• SQL
• Fivetran
• Apache Airflow
• Azure Data Factory
• AWS
• Azure
• Google Cloud
• Snowflake
• Motherduck
• Spark Streaming
• Kafka
• Claude Code
• CoPilot
• Codex

Benefits

• Competitive pay
• Excellent benefits

Physical Requirements

• Frequent sitting at a desk performing work on a computer
• Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions

Core Values

• Take the long view to build a lasting organization
• Be courageous and make the right decisions even when challenging
• Be genuine and bring honesty to all interactions
• Work with focus and passion, taking pride in your work and continual learning