Who We Are
Vultr is on a mission to make high-performance cloud infrastructure easy to use, affordable, and locally accessible for enterprises and AI innovators around the world. With 33 global cloud data center locations, Vultr is trusted by hundreds of thousands of active customers across 185 countries for its flexible, scalable, global Cloud Compute, Cloud GPU, Bare Metal, and Cloud Storage solutions. In December 2024 Vultr announced an equity financing at a $3.5 billion valuation. Founded by David Aninowsky and self-funded for over a decade, Vultr has grown to become the world’s largest privately-held cloud infrastructure company.
Vultr Cares
100% company-paid insurance premiums for employee medical, dental and vision plans.
401(k) plan that matches 100% up to 4%, with immediate vesting
Professional Development Reimbursement of $2,500 each year
11 Holidays + Paid Time Off Accrual + Rollover Plan
Commitment matters to Vultr! Increased PTO at 3 year and 10 year anniversary + 1 month paid sabbatical every 5 years + Anniversary Bonus each year
$500 stipend for remote office setup in first year + $400 each following year
Internet reimbursement up to $75 per month
Gym membership reimbursement up to $50 per month
Company paid Wellable subscription
Join Vultr
Vultr is building a trusted enterprise data foundation in Google BigQuery. As our first dedicated Senior Data Engineer, you will build and operate the pipelines, transformations, and quality controls that turn operational data into reliable datasets for reporting and analytics.
You will work with BI, data science, business system owners, and Engineering. Engineering owns product data and source instrumentation; you will partner with them to bring that data into enterprise analytics. You will help shape data engineering standards within Vultr’s enterprise architecture.
Key Responsibilties
Build and operate pipelines from operational systems into BigQuery, using incremental loading and change data capture where appropriate.
Develop bronze, silver, and gold datasets, including shared business entities and reporting metrics.
Automate data validation and source-to-target reconciliation. Ensure updates, deletes, and historical source corrections reach downstream datasets.
Monitor pipeline health, handle exceptions and schema changes, and document recovery procedures and lineage.
Partner with BI and data science teams to deliver documented, performant datasets.
Work with Engineering and business system owners to resolve source-data gaps and define reliable data handoffs.
Propose and implement data engineering standards for testing, deployment, security, and cost management within the agreed enterprise architecture.
What success looks like
In your first several months, you will assess existing pipelines, establish repeatable engineering practices, and deliver production datasets for priority reporting needs. You will put initial quality controls and monitoring in place and demonstrate that historical source corrections are reflected accurately in downstream reporting.
Required qualifications
5+ years of data engineering experience, including ownership of production pipelines.
Advanced SQL and strong Python skills.
Production BigQuery experience, including partitioning, clustering, query performance, and cost management.
Experience with data transformation and orchestration tools such as dbt, Airflow, Cloud Composer, Dagster, or equivalents.
Experience extracting from operational databases and handling incremental loads, updates, deletes, backfills, and historical corrections.
Strong understanding of dimensional modeling and historical data tracking.
Experience with automated data quality checks, reconciliation, monitoring, alerting, and recovery.
Experience with Git, code review, automated testing, and CI/CD.
Ability to work across Engineering, analytics, and business teams.
Preferred qualifications
Experience with MySQL, ClickHouse, Kafka, or Google Pub/Sub.
Familiarity with Parquet, storage efficiency, and Spark or PySpark.
Ability to trace data definitions and business logic through application code or an ORM; familiarity with PHP is a plus.
Experience with Salesforce, NetSuite, Power BI, or comparable systems.
Familiarity with IAM, service accounts, least-privilege access, and secure workload authentication.
Experience with metadata, lineage, or data observability tools.
Experience applying AI or automation to pipeline operations, incident investigation, or governed data access for LLM applications.
Experience in cloud infrastructure, telecommunications, data centers, or another asset-intensive environment.
Our environment
Our data environment includes Google BigQuery, MySQL, ClickHouse, Kafka, Python, Power BI, Salesforce, and NetSuite. Engineering also stores some Prometheus-format metrics in Grafana Mimir and ingests them into ClickHouse. This role will partner with Engineering to bring relevant product data into governed enterprise datasets and help standardize how those datasets are transformed, tested, and operated.
Compensation
$155,000 - $180,000
Final compensation will vary depending on years of experience, background/skill set, location, and applicable laws.
Inclusion & Privacy
We are an equal opportunity employer and are committed to creating an inclusive environment for all employees. We welcome applications from individuals of all backgrounds and experiences, and we prohibit discrimination based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status under applicable laws. Vultr will consider qualified applicants with arrest or conviction records in accordance with applicable laws and will not conduct a background check until after an offer of employment has been extended and accepted.
We also take your privacy seriously. We handle personal information responsibly and follow applicable laws, including U.S. privacy rules and India’s Digital Personal Data Protection Act, 2023. Your data is used only for legitimate business purposes and is protected with proper security measures.
Where allowed by law, applicants may request details about the data we collect, access or delete their information, withdraw consent for its use, and opt out of nonessential communications. For more details, please see our Privacy Policy.
5+ years data engineering experience, advanced SQL and Python, production BigQuery, dbt/Airflow/Cloud Composer/Dagster, dimensional modeling, automated quality checks, Git/CI/CD, and cross-team collaboration.
Key Responsibilities
- building pipelines
- transforming data
- monitoring quality
Skills & Tools
Google BigQuery, SQL, Python, dbt, Airflow, Cloud Composer, Dagster, Git, MySQL, ClickHouse, Kafka, Google Pub/Sub, Parquet, Spark, PySpark, PHP, Salesforce, NetSuite, Power BI, IAM, Grafana Mimir
Job Details
- Category: Data and Analytics
- Seniority: Senior Level
- Commitment: Full Time
- Workplace: Remote — United States
- Salary: USD 155,000 – 180,000 / year
- Languages: English
Benefits
- 401k matching
- Generous paid time off
- Tuition reimbursement
- Retirement plan
About Vultr
A cloud infrastructure company providing high-performance compute, GPU, bare metal, and storage solutions globally. — Industry: Information Technology