Senior Data Engineer - Data Intelligence - Data Products at Culture Amp

Melbourne, Victoria, Australia -

Full Time

Start Date

Immediate

Expiry Date

29 Apr, 26

Salary

0.0

Posted On

29 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Data Modelling, Python, Data Processing, Pipeline Development, Analytical Databases, Streaming Data, Event-Driven Architectures, Collaboration, Statistical Models, Machine Learning, Data Transformation, Schema Design, Query Performance, Complex Queries, Data Insights

Industry

Software Development

Description

Join us on our mission to make a better world of work. Culture Amp is the world’s leading employee experience platform, revolutionizing how 25 million employees across more than 6,500 companies create a better world of work. Culture Amp empowers companies of all sizes and industries to transform employee engagement, drive performance management, and develop high-performing teams. Powered by people science and the most comprehensive employee dataset in the world, the most innovative companies including Canva, On, Asana, Dolby, McDonalds and Nasdaq depend on Culture Amp every day. Culture Amp is backed by leading venture capital funds and has offices in the US, UK, Germany and Australia. Culture Amp has been recognized as one of the world’s top private cloud companies by Forbes and most innovative companies by Fast Company. For more information visit cultureamp.com. How you can help make a better world of work We're building the analytics foundation for Culture Amp's next generation of workforce insights. This is a hands-on Senior Data Engineer role in our Data Products team, focused on data modelling and analytical query design at scale. What you'll do You'll design and build the data models that power insights connecting engagement, performance, hierarchy and retention data. The goal is helping leaders understand not just what's happening in their organisation, but why. This means: Building analytical data models in ClickHouse, optimised for complex queries across millions of survey responses and workforce events Designing schemas and transformations that make it easy to compute insights across multiple data domains Collaborating with data scientists to bring statistical and ML models into production Working with streaming data pipelines (Kafka) to ensure data lands in the right shape for analytical workloads What makes this interesting This work is central to Culture Amp's product strategy. We have one of the largest workforce datasets in the world: years of engagement surveys, performance cycles, and organisational changes across thousands of companies. The technical challenge is making that data queryable, joinable, and useful for insights that actually matter to customers. You'll be building something new, not maintaining legacy systems. The insights platform is greenfield work on modern infrastructure (ClickHouse, Kafka, dbt), solving genuinely hard problems around statistical validity at scale and real-time analytics. You Have Strong SQL and data modelling skills. You think in sets, understand query performance, and can design schemas that balance flexibility with efficiency. Strong Python skills for data processing and pipeline development Experience with analytical databases (ClickHouse, BigQuery, Snowflake, or similar) Familiarity with streaming data and event-driven architectures Ability to work closely with data scientists. You don't need to build the models, but you need to understand what they need from the data layer. Comfort with ambiguity. This is discovery-heavy work where requirements evolve as we learn what's possible. You are Self-motivated and able to work independently, comfortable dealing with ambiguity when necessary. You take the initiative to ensure that you have everything you need to work effectively and ask for support when required. A driver of technical excellence in a team environment. You’re an expert in your domain and are able to develop the expertise and knowledge of those around you. Someone who loves collaboration - our teams are cross functional and you’ll be working with other engineers, team leads and product managers to deliver great outcomes together. Aligned with our values, check them out here: https://www.cultureamp.com/company#values and demonstrate them through your working practice. We believe that our employees are the heartbeat of our success. We're committed to fostering a work environment that truly cares for and develops its people, and creates lasting positive impact. In addition to providing a competitive compensation package, some of the key benefits we offer are: Employee Share Options Program: We empower you to be an owner in Culture Amp and share in our success Programs, coaching, and budgets to help you thrive personally and professionally Access to external providers for mental wellbeing and coaching support to sustain the wellbeing, safety and development of our people Monthly Camper Life Allowance: An automatic allowance paid out each month with your pay - you can spend it however you like to help improve your experience and life outside work Team budgets dedicated to team building activities and connection Intentional quarterly wellbeing pauses: A quarterly company-wide shutdown day in each region to to collectively pause, reset and focus on restoration and rest, without having to tap into individual vacation time Extended year-end breaks: An extended refresh period at the end of year Excellent parental leave and in work support program available from day 1 of joining Culture Amp 5 Social Impact Days a year to make a positive impact on the community outside of work MacBooks for you to do your best & a work from home office budget to spend on setting up your home office Medical insurance coverage for you and your family (Available for US & UK only) Additionally, we don't just focus on our internal community; we believe in creating a better world of work for all. We're committed to diversity, equity, and inclusion, with Employee Resource Groups and ally communities in place. We have a strong commitment to Anti-Racism, and endeavor to lead by example. Every step we make as a business towards anti-racism is another step we can take to support our customers in making a better world (of work). You can see our current commitments to Anti-Racism here. Please keep reading... Research shows that candidates from underrepresented backgrounds often don't apply for roles if they don't meet all the criteria – unlike majority candidates meeting significantly fewer requirements. We strongly encourage you to apply if you’re interested: we'd love to know how you can amplify our team with your unique experience! If you decide to apply, as part of your application, we will ask you to complete voluntary diversity questions (excluding roles in Germany). These questions are completely optional, but your participation truly helps. By sharing this anonymous information, you support our efforts to build a more inclusive and equitable hiring process—and help us hold ourselves accountable to that commitment. Your responses are entirely confidential and will not impact hiring decisions. If you require reasonable accommodations or adjustments due to a disability to complete the online application or to participate in the interview process, please contact accommodations@cultureamp.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly. Culture Amp will retain your CV & personal information for a period of two years (four years for the US) from the date of your application process completion. Culture Amp may contact you in relation to future job opportunities during this time period. For further information please see our privacy policy here or contact privacy@cultureamp.com.

Responsibilities

Design and build data models that connect engagement, performance, hierarchy, and retention data. Collaborate with data scientists to bring statistical and machine learning models into production.