Senior Data Engineer (AWS + Snowflake)

The part you'll play and why it matters Docuvera’s building products where generative AI and great analytics actually work in the real world, and we need a Senior Data Engineer to help make that possible. In this role, you’ll set up and lead our Data Engineering program: the platform, the standards, the culture, and the momentum. You’ll design and build the data foundations that power our natural language + generative AI features, while also leveling up our reporting, insights, and analytics across teams. You won’t be stuck in a corner “just doing pipelines.” You’ll own end-to-end delivery, partner closely with product/engineering/customer teams, and help us ship complex solutions for international customers — reliably, securely, and at scale. You’ll help Docuvera grow faster by building the kind of trusted, scalable data foundation that lets teams move quickly without breaking things. That means: cleaner, more reliable data a platform that scales with customers and use cases faster decision-making across the business less delivery friction (and fewer “why is this number different?” conversations) strong foundations for high-performing GenAI features and dependable analytics What you’ll focus on You’re the type of person who enjoys taking messy, complex data systems from idea → build → run → improve. You’ve got strong transformation skills (wrangling, aggregation, modelling, visualization-ready datasets, ML-ready datasets), and you genuinely like enabling other teams with better data. You’re organized, proactive, and comfortable owning things, but you also enjoy building alongside others and lifting capability across the team. Here’s the kind of work you’ll be owning: Own the end-to-end data platform on AWS + Snowflake — ingestion (S3, Kinesis, Glue), ELT (dbt), orchestration (Step Functions), serving layer Build batch + streaming pipelines for multi-client document ingestion at scale using Apache Iceberg on S3, exposed natively into Snowflake (including late-arriving data + at-least-once guarantees) Build the ML data infrastructure: feature engineering pipelines, a versioned feature store, SageMaker integration, plus the embedding + vector storage layer that powers our RAG-based GenAI features Set up data quality + observability (and do real root-cause work when things go wrong so we don’t repeat the same issues) Make sure we’re doing data security properly: GDPR, data residency, IAM least privilege, secrets management, row/column-level access controls in AWS + Snowflake Help build a high-performing Data Engineering function: standards, mentoring mid-level engineers, CI/CD for pipelines, infrastructure-as-code practices Design and maintain Snowflake data models using Kimball principles (facts/dims, SCDs, conformed dimensions) for analytics + ML consumption What you’ll bring You’ve probably done a lot of this already, and you’re ready to own it end-to-end: Strong hands-on AWS experience: S3, Glue, Kinesis, Lambda, SQS, IAM, CloudWatch Deep Snowflake experience: schema design, performance tuning, streams + tasks, clustering, masking + row-level security Solid experience with Apache Iceberg in an S3-based lake setup, including exposing Iceberg tables to Snowflake (external tables or native Iceberg support) Advanced SQL + strong dbt/ELT design skills, and real-world batch/streaming experience (late data, at-least-once delivery, etc.) Kimball dimensional modelling know-how (facts/dims, SCD Type 1/2/3, conformed dimensions) in Snowflake IaC + CI/CD experience (Terraform or AWS CDK), plus familiarity with observability tools like Great Expectations / Monte Carlo (or similar) Experience supporting ML + GenAI data needs: feature stores, embedding pipelines, SageMaker integration, RAG-friendly data engineering Good grasp of multi-region governance/compliance: right-to-erasure, residency enforcement, audit logging, secrets management Comfortable leading: setting standards, mentoring, and explaining trade-offs clearly to non-technical stakeholders What we'll expect of you We value diversity of experience, perspective, and background and we recognise that how we work is just as important as what we achieve. We’re built around a few consistent ways of working: driving outcomes, innovating, lifting others up, adapting quickly, leading by example, and bringing people together around a shared purpose. What we expect technically: Significant experience in software engineering within modern product environments Strong proficiency in contemporary programming languages and frameworks Experience designing and building scalable distributed systems or cloud-native applications Solid understanding of software architecture, testing, security, and engineering best practices Ability to balance technical quality with commercial and delivery outcomes How we expect you to show up day to day: Focus on what matters most and drives results without chasing perfection Be curious, proactive, and always looking for better ways to do things Lift others up through listening, collaboration, and crediting contributions Stay positive and calm through change and helps others find clarity and momentum Lead with initiative and accountability, communicating early and acting in the team’s best interests Bring steadiness and purpose, uniting people around shared goals with optimism, professionalism, and integrity What you can expect from us We want people to do meaningful work, have a visible impact, and keep growing their careers. You can expect to join a collaborative, down to earth team, where good ideas are valued, people have genuine ownership, and influence is not limited by hierarchy. You’ll work on interesting technical challenges that have meaningful customer impact, particularly in highly regulated industries where quality, trust, and compliance genuinely matter. We are a distributed global team, but we work hard to stay connected. Our culture is built on curiosity, initiative, transparency, and continuous improvement. We focus on outcomes, accountability, and progress rather than where you work or how visible you are. You can also expect: a range of leave benefits, including year-end appreciation leave, birthday leave, parental leave, long-service leave, and the use of confidential, fully funded employee assistance support. Other entitlements may vary depending on location and eligibility (such as unlimited PTO and healthcare benefits for the US). genuine flexibility and trust in how you manage your work, helping you balance professional and personal commitments the tools and support to do your best work. This includes heavy investment modern systems and AI-enabled technology, the autonomy to improve processes, and opportunities to help shape how work evolves as we grow. access to funded and free learning and professional development opportunities, and a company with a strong track record of internal progression. Why Docuvera? Docuvera is the industry leader in governed, structured content authoring for the Pharma industry and as a pioneer in this space, we are proud to support top global Pharma companies. Born out of Author-it in 2017, we are on a mission to help our customers harness the power of digital innovation, accelerating their ability to safely get their life changing products to market faster. Docuvera empowers life sciences organisations to drive digital transformation in how they manage their content. Docuvera turns content into small, reusable ‘building blocks’ (components). You write and approve a block once, then reuse it confidently across many documents and projects, keeping everything consistent across documents, products, and regions. For our team, it means delivering real-world impact through ground-breaking solutions to technically complex problems. We're a global team working across New Zealand, Asia, the UK, Europe, and the United States, and Docuvera is now a member of the cormeo family of companies, an exciting step that strengthens our global reach and long-term growth. Keen to know more? Check out the careers page for more information about working with us, and follow us on LinkedIn to check out what we've been up to recently. _____________________________________________________________________________ Key information about our recruitment process If there’s anything we can do to make our recruitment process more inclusive or accessible for you, please let us know. We’re happy to accommodate where we can. We use AI tools to complement our recruitment process. We may use AI to support certain stages of the hiring process, such as reviewing applications, analysing resumes, or evaluating responses but they do not replace human interaction or decision making. All final hiring decisions are made by our people. Our process usually includes two online interviews, each about an hour long, with one or two members of our team. Some roles may also include a technical exercise to help us understand your approach and skills. We’ll also ask for at least two professional references and complete a background and/or verification check. We’ll keep applications open until we find the right person, and we’ll keep you updated along the way. For recruitment agencies: we work with a select group of preferred partners, so please don’t send unsolicited CVs as we won’t be able to consider them.