Senior Data Engineer

Kavyos Consulting; New York (NY); On-site; USD 140,000 - 190,000; Full time

Job summary

Kavyos Consulting is building a modern cloud-native data platform on Google Cloud and seeks a hands-on Senior Data Engineer to own the transformation layer from raw source data through analytics-ready models that power business reporting and decision-making.

You will design, build, and maintain layered data pipelines, improve reliability with CI/CD, and partner with analysts to deliver trusted data while shaping our architecture as we scale.

Qualifications

• 3+ years in data engineering or analytics engineering.
• Hands-on BigQuery, Snowflake, or Redshift experience in production.
• Experience with a SQL-based transformation framework - Dataform or dbt Core.
• Strong SQL - window functions, CTEs, complex joins, performance optimization.
• Python proficiency - data pipelines, scripting, automation.
• Data modeling fundamentals - staging layers, dimensional modeling, fact and dimension tables.
• Experience with data ingestion or CDC pipelines into a cloud warehouse.
• Strong communication skills - explain data models to non-technical stakeholders.
• Entrepreneurial, builder mindset - comfortable with ambiguity and evolving requirements.

Responsibilities

• Design, build, and maintain layered data transformation pipelines in BigQuery (staging, integration, warehouse).
• Ensure pipeline reliability through automated testing, CI/CD with Git-based workflow, scheduling, and monitoring.
• Optimize cloud data warehouse performance and compute costs (partitioning, clustering, slot usage).
• Collaborate with analysts and BI developers to deliver trusted, well-documented data.
• Contribute to platform and tooling decisions as we mature our data infrastructure.

Skills

SQL

Python

Data modeling

Data pipeline design

Communication

Entrepreneurial mindset

Tools

BigQuery

Snowflake

Redshift

Dataform

dbt Core

Git

Job description

We are building a modern cloud-native data platform on Google Cloud and looking for a hands‑on Senior Data Engineer to own the transformation layer from raw source data through to analytics‑ready models that power business reporting and decision‑making. Our stack and processes are still evolving, so you'll help shape architecture and standards, not just inherit them.

What You’ll Do

• Design, build, and maintain layered data transformation pipelines in BigQuery (staging, integration, warehouse/mart models)
• Ensure pipeline reliability through automated testing, CI/CD with Git-based development workflow, scheduling, and monitoring
• Optimize cloud data warehouse performance and compute costs (partitioning, clustering, slot/usage management)
• Collaborate with analysts and BI developers to deliver trusted, well‑documented data
• Contribute to platform and tooling decisions as we mature our data infrastructure

What You’ll Bring

• 3+ years in data engineering or analytics engineering
• Hands‑on BigQuery (preferred), Snowflake, or Redshift experience in production
• Experience with a SQL‑based transformation framework - Dataform or dbt Core
• Strong SQL - window functions, CTEs, complex joins, performance optimization
• Python proficiency - writing clean, reusable code for data pipelines, scripting, and automation
• Data modeling fundamentals - staging layers, dimensional modeling, fact and dimension tables
• Experience with data ingestion or CDC pipelines into a cloud warehouse
• Strong communication skills - able to explain data models, trade‑offs, and pipeline issues clearly to non‑technical stakeholders, including senior leadership
• An entrepreneurial, builder mindset - comfortable with ambiguity, evolving requirements, and making pragmatic decisions when the playbook doesn't exist yet
• Strong critical thinking and problem‑solving - you question source data, challenge requirements, and translate ambiguous business problems into well‑structured data models rather than building the ticket as written

Nice to have

• E-commerce or grocery/retail domain experience
• Familiarity with marketing analytics data such as campaign, CRM, clickstream, or event‑tracking data (e.g., Braze, Mixpanel, GA4)
• Experience with a BI tool (Power BI, Tableau, Looker)