Senior Analytics Engineer at Velir

Job description

Velir is an established mid-sized agency with a top-tier portfolio of clients, ranging from the world’s largest non-profits to Fortune 500 brands. As of 2023, Velir acquired Brooklyn Data Company, a premier data and analytics consultancy focused on leadership, process improvement, implementation, and advanced analytics. At Velir, we believe people are our greatest asset. Our culture is built on a foundation of trust, collaboration, and continued improvement. We strive for excellence in everything we do, embracing challenges as opportunities for growth. Our success is driven by a shared passion for making a positive impact on our customers, our communities and each other. We are a remote first company that offers competitive pay and excellent benefits. Overview At Brooklyn Data, Senior Analytics Engineers lead the design and implementation of scalable data models and pipelines that turn complex data into clear, trustworthy insights. They work closely with functional leadership and data solutions partners to shape data architectures and modeling strategies that align with client goals and deliver measurable impact. Because our clients are mostly US-based organizations, we look for the ability to communicate with professional proficiency in English, verbally and in writing. Responsibilities Engineering Leadership Lead complex technical implementations, shaping data architecture and transformation pipelines that prioritize performance, maintainability, and reusability. Drive adoption of best practices for dbt development, testing, and CI/CD while mentoring peers through code reviews, pairing, and technical guidance. Contribute to internal tooling, shared dbt packages, and scalable frameworks that raise the standard of analytics engineering across teams and clients. Cross-Team Collaboration Partner with analysts, engineers, and stakeholders to translate complex and often ambiguous business requirements into well-structured data models and semantic layers. Serve as a technical and strategic advisor in cross-functional planning—balancing stakeholder requirements, data governance, and long-term scalability. Model strong communication and mentorship, helping other AEs and cross-functional teammates develop clarity and confidence in data architecture decisions. Project Enablement Lead end-to-end delivery of analytics engineering workstreams, ensuring solutions are reliable, well-documented, and aligned with client objectives. Anticipate and address systemic data quality or modeling issues, implementing durable solutions that improve trust and efficiency across the stack. Enable sustainable project delivery by optimizing performance, reducing technical debt, and contributing to shared standards that scale across teams. Skills & Qualifications Programming languages (e.g., SQL, Python) Business intelligence platforms (e.g., PowerBI, Sigma) Expert proficiency in dbt is required. Expert proficiency in data modeling approaches and philosophies (e.g., Kimball, OBT) Expert proficiency with at least one cloud data warehouse (e.g., Snowflake, BigQuery) Expert proficiency with version control and git. Knowledge of common data integration patterns (e.g., CDC, ELT, etc.) Knowledge of common data integration / orchestration platforms (e.g., Fivetran, Dagster, Apache Airflow) Ability to communicate with professional proficiency in English, verbally and in writing. Bonus points for: Strong analytical instincts—you can spot patterns, anomalies, and relationships across large, complex datasets. Experience working with event-driven data pipelines or pub/sub architectures to move and process data efficiently across systems. Experience using AI or automation tools to enhance analytics engineering workflows—whether for testing, documentation, or performance optimization. Physical Requirements Frequent sitting at a desk performing work on a computer Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions Compensation Range: $135,000 - $150,000 annually Please note that compensation packages are finalized after the interview process is concluded. We use a competency-based approach to base pay, which means it is based on the competencies and skills demonstrated for this role. Core Company Values Take the Long View - Ensure the company is built to last Be Courageous - Make the right decisions even when they aren't the easiest decisions Be Genuine - Bring honesty and authenticity to all that you do Work with Focus + Passion - Display purpose and pride in your work and never stop learning As an equal opportunity employer, we are firmly committing to diversity, equity, and inclusion in our hiring efforts. We recognize that we need team members from all backgrounds and experiences to successfully shape a positive employee experience as well as deliver our product and service solutions. To that end, we actively seek candidates who can bring diverse experiences and backgrounds to our team. We know that complex factors and systemic bias can get in the way of us meeting strong candidates, so please don't hesitate to apply even if you're not 100% sure. At this time, Velir does not sponsor candidates and unfortunately cannot accept those on OPT or CPT.

Requirements

Must-haves

Engineering Leadership
Lead complex technical implementations, shaping data architecture and transformation pipelines that prioritize performance, maintainability, and reusability.
Drive adoption of best practices for dbt development, testing, and CI/CD while mentoring peers through code reviews, pairing, and technical guidance.
Contribute to internal tooling, shared dbt packages, and scalable frameworks that raise the standard of analytics engineering across teams and clients.
Cross-Team Collaboration
Partner with analysts, engineers, and stakeholders to translate complex and often ambiguous business requirements into well-structured data models and semantic layers.
Serve as a technical and strategic advisor in cross-functional planning—balancing stakeholder requirements, data governance, and long-term scalability.
Model strong communication and mentorship, helping other AEs and cross-functional teammates develop clarity and confidence in data architecture decisions.
Project Enablement
Lead end-to-end delivery of analytics engineering workstreams, ensuring solutions are reliable, well-documented, and aligned with client objectives.
Anticipate and address systemic data quality or modeling issues, implementing durable solutions that improve trust and efficiency across the stack.
Enable sustainable project delivery by optimizing performance, reducing technical debt, and contributing to shared standards that scale across teams.
Skills & Qualifications
Programming languages (e.g., SQL, Python)
Business intelligence platforms (e.g., PowerBI, Sigma)
Expert proficiency in dbt is required.
Expert proficiency in data modeling approaches and philosophies (e.g., Kimball, OBT)
Expert proficiency with at least one cloud data warehouse (e.g., Snowflake, BigQuery)
Expert proficiency with version control and git.
Knowledge of common data integration patterns (e.g., CDC, ELT, etc.)
Knowledge of common data integration / orchestration platforms (e.g., Fivetran, Dagster, Apache Airflow)
Ability to communicate with professional proficiency in English, verbally and in writing.
Strong analytical instincts—you can spot patterns, anomalies, and relationships across large, complex datasets.
Experience working with event-driven data pipelines or pub/sub architectures to move and process data efficiently across systems.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

ci/cdsqlpythonai

Platform: greenhouse
Effort: quick