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We are looking for a hands-on, proactive DBA to join our growing SASE R&D DevOps group. As our dedicated Database Administrator, you will own the operational and performance aspects of our database stack and work closely with R&D engineers, SREs, and QA to ensure our data layer is resilient, efficient, secure, and scales with our business.

This is not a siloed infrastructure-only role - you will partner deeply with developers from design to production, provide input on data modeling and query optimization, and ensure best practices across the board, from schema design to observability, disaster recovery, and upgrades.

We are in a period of hyper-growth - both in terms of customer adoption and engineering scale. This brings exciting challenges in performance, scalability, cost-efficiency, and reliability. Youll play a key role in shaping how our data infrastructure supports this scale and future-proofs our platform.

Why Join Us

Be a core player in our hyper-growth journey - influencing how we scale our platform to support growing enterprise demand.
Collaborate with a top-tier R&D team building a modern, cloud-native SASE platform.
Take real ownership of mission-critical systems in an environment that values technical excellence and impact.
Key Responsibilities
Own and operate production and pre-production databases, including:
MongoDB (Atlas)
Redis (AWS ElastiCache Valkey)
RabbitMQ (EC2-based cluster)
Additional databases as our platform evolves
Work closely with developers to optimize data models, indexes, and queries across the SDLC (design, QA, staging, production).
Partner with SREs to ensure high availability (99.99% uptime), disaster recovery, monitoring, and performance tuning.
Plan and execute schema changes, index strategies, and database version upgrades with zero or minimal downtime.
Set up and enforce backup, restore, and retention policies aligned with compliance and availability needs.
Implement and maintain observability tools and alerting for the data infrastructure.
Lead cost optimization of all data services rightsizing, usage analysis, cleanup, and architecture alignment.
Troubleshoot and resolve data-related incidents; participate in on-call rotations and post-mortems as needed.

Similarweb is the leading digital intelligence platform used by over 3500 global customers. Our wide range of solutions power the digital strategies of companies like Google, eBay, and Adidas.

We help our customers succeed in todays digital world by giving them access to data-driven insights, competitive benchmarks, strategic analysis, and more.

In 2021, we went public on the New York Stock Exchange, and we havent stopped growing since!

Were looking for a Data Scientist to join our Data Labs department, which specializes in professional services for our super premium customers.

This role will report to our Datalabs Team Manager in the, R&D.


Why is this role so important at Similarweb?

Similarweb is a data-focused company, and our unique AI and machine learning capabilities are the center of our business.

As part of this role, you will create data models that help analyze the petabytes of data we receive from various sources, and research and develop new features and capabilities for our product solutions

As a data scientist in the Datalabs team, you will work on the very core of the company. Part of your role will be to turn raw data into usable metrics and develop new models and statistical algorithms to support out-of-the box requests from customers who want custom digital insights. The Datalabs departments customer centric and business-oriented nature also means you will be supporting a team of data analysts and consultants who interact directly with customers. Together with them, you will translate the voice of these customers into best-in-class digital insights.

So, what will you be doing all day?

Your role as part of the R&D department, and as part of the Datalabs team means your daily responsibilities may include:

Working on versatile use cases within a dynamic, fast paced production environment
Strategic thinking and problem solving, with a strong business sense
Analyzing data from various sources, and turning it into usable input
Understanding various use cases from different customers, and creating models that can translate these cases into meaningful insights
Initiating newly defined tasks from exploration to proof of concept
Owning the finalization of defined tasks (from POC to deployment in production)
Collaborating with data engineers to make sure we reach the desired production results
Owning the ongoing validation process for existing metrics
Collaborating and brainstorming best practices with other teams within the R&D department
Deploying machine-learning models into production for an ongoing use