Data Engineer

Koa Health is a fast-growing digital technology company focused on delivering innovative digital mental health solutions to healthcare providers. We are revolutionising mental health care by delivering therapeutic solutions through smartphones. Our mission is to make mental health support accessible, personalised, and effective by leveraging cutting-edge technology and data. We have made it our goal to combine the best research and technology to help people improve their mental health using a digital-first approach. Our market-leading evidence base shows that we have succeeded.

Having recently, successfully, secured Series B funding and as the demand for our services continues to grow, so must our teams. We are therefore now seeking an accomplished Data Engineer to join our Data Team and embark on this exciting and critical moment in Koa Health’s journey.

Your new role:

As a Data Engineer within the Data Team at Koa, your main focuses and responsibilities will be the following ones: 

• Data Products Development: Build and maintain scalable products, such as APIs accessing data from the datalake, and reporting tools for self-service analytics for external customers. Rethink and contribute to the definition and development of a scalable data architecture supporting the iteration of such data products.
• Code Quality: Maintain coding standards and best practices, prioritising clean, production-ready code, and treating data pipelines as a final product for internal and external customers. Apply modular design principles, creating components that can be adapted to new data sources or new transformations. (python, scala, SQL).
• Data Ingestion and APIs: Build and maintain ingestion pipelines in our AWS datalake, integrating new data sources, both SQL and noSQL, pulling data via APIs for integration with various systems, such as NetSuite, Hubspot, and other external clinical partners.
• New Tools exploration: Investigate and implement tools, with special focus on the AWS suite (like Athena, Lake Formation, Glue, DMS, AppFlow), to enhance platform scalability, accessibility, and compliance with strict privacy regulation.
• Data Pipelines framework: contribute to our work-in-progress framework to develop scalable, reliable, and maintainable data pipelines, using tools such AWS Glue, Step Functions, and Airflow. Advocate for data pipeline best practices, including idempotency:  to handle reprocessing of historical data efficiently, ensuring data integrity (no duplicate effect, and reproducibility).
• Self-service analytics: Optimize and extend the use of our recently introduced BI tool, Superset, ensuring seamless integration with our data stack, to deliver scalable self-service reporting solutions for customers. Ensure the BI platform aligns with Koa data governance and security standards, while enabling flexibility for ad-hoc reporting and analysis.
• Custom datasets and Dashboards: Create tailored datasets to support product and other business functions. Develop and maintain automated reports, analyses, and dashboards to monitor the performance of key product features, ensuring that stakeholders have access to the most updated and reliable insights.

As a secondary responsibility, you may also contribute to the following ongoing activities and streamlines:

• Data Quality frameworks: Improve data quality by improving schema validation during data ingestion. Detects and flag issues such as missing fields, incorrect types, or schema mismatches at the source. Develop automated tests and quality checks integrated into pipelines, covering data completeness and consistency, both across ingestion and processing layers.
• Observability frameworks: Integrate monitoring tools such as Amazon CloudWatch, Datadog, and Spark UI logs to provide comprehensive visibility into the platform's health. Aggregate logs from various sources (e.g., Spark application logs, CloudWatch logs) into centralised systems like Datadog for unified analysis, and create dashboards and alerting rules for critical events, such as job failures, task delays, resource bottlenecks, and pipeline errors.
• Stakeholder Support: Provide support to Sales, Marketing, Clinical teams, and other key stakeholders, by delivering internal data product and business KPIs. This includes the development of automated reporting systems to ensure seamless access to critical metrics.
• Collaborate with Product Teams: Work closely with product teams, ideally as an embedded member, to ensure a data-driven approach is integrated into every aspect of product development and strategy.
• Define Analytics Tracking: Lead the definition and implementation of analytics tracking for in-app events, particularly when new features are developed, new pages are added, or new clients are onboarded.
• ML/AI Use Case Development: Collaborate closely with the R&D team to identify, design, and develop machine learning and AI use cases. 

You will have:

• Programming Skills: Highly proficient in Python, specially PySpark (for data engineering and analytics jobs), SQL (advanced querying, and optimization), Nice-to-have: Scala.
• Data Engineering experience: 3+ years of experience in Data pipelines development (e.g. AWS Glue, Airflow, DBT or similar). Ideally, working with event-driven architectures (Kinesis, Kafka).
• AWS Expertise: 3+ years of experience working with at least some of the AWS services for data development (e.g. S3, Athena, Lake Formation, Glue, Step Functions, EMR, AppFlow, DMS, etc.).

Nice-to-have:

• Business Intelligence & Visualisation: Experience building dashboards with a BI tool (such as Superset, Tableau, Metabase). Nice-to-have: familiarity with visualisation libraries, such as Plotly.
• Analytics engineering experience: Experience of creating modular, version-controlled, and testable pipelines that are usable both for data experts and for final stakeholders (e.g. datamarts, datawarehouse, reporting layers…)
• Product Analytics: Experience with in-app analytics tracking, A/B testing methodologies and frameworks to assess the impact of product changes.

Soft Skills:

• Product-driven: you embrace an iterative approach to product development, focusing on continuous trade-offs between tailored solutions and scalable architectures that align with evolving  business needs.
• Communication: You are able to collaborate across both business teams (product, sales, marketing, customer success) and engineer teams (DevOps, Cyber, Pods engineers), explaining technical concepts to non-technical stakeholders, and filling the gap between these two groups.
• Growth mindset: You love debugging data pipeline issues, advocating for data quality, as much as for continuously improving code quality. You see a bug or an error as an opportunity to learn and improve our processes, pipelines and products.
• Team Player: Strong collaborator, open to learning beyond their comfort zone, and dedicated to mentoring team members to enhance coding skills and best practices.

About Koa Health 

Against the backdrop of decades of rising demand, mental health has never been more important.  The Covid pandemic has led to a four-fold increase in mental disorders around the world, impacting individuals, companies, and communities. 

Today, we simply don’t have enough mental health clinicians to meet demand.  Koa Health aims to solve the gap between demand and supply with a unique human-digital hybrid approach, built upon the best digital technology.  Koa’s digital assets deliver the highest quality care, measured through engagement, program completion, patient and clinician satisfaction. Koa technology substantially increases clinician productivity, allowing our precious clinicians to treat more people. 

Having secured a successful and oversubscribed Series A funding totaling €30m (ca.$36M) in October 2020 and additional €20m funding in May 2022, we are currently closing our Series B round of investment, with €12M secured from our existing investors.  You can read more about Koa Health on our website here.  There has never been a more critical time for the work that we’re leading at Koa Health.  And this is where you come in!  

Why Koa Health?

We are at the forefront of innovation in digital health, working on one of today’s hottest topics – mental health.  By working with Koa, you will make a positive impact on the lives of many people.

Aside from the power of our mission, we provide all the support and benefits to make your life at work and outside of work fun and comfortable year-round, such as:

• Competitive rewards package that includes: Food Allowance, Private Health Insurance, Pension Contribution, Life Insurance, Bonus Scheme, and Share Options
• We believe in walking the talk: We are focused on supporting your wellbeing and therefore provide you with a Wellbeing Allowance and Wellbeing Leave, as well as a generous annual leave allocation to help manage both your mental and physical health as you see fit
• Flexibility: We’re hiring your skills and experience, so ask you to use these in the most effective way you can whilst managing your work-life balance in your own way
• An international environment: Our teams, our clients and our collaborators span the US, the UK, Europe, and Asia.  Our breadth of experience offers the opportunity to understand and get involved in healthcare systems worldwide.

An inclusive workplace

We firmly believe that diversity and inclusion should be embedded in the fabric of our organization and we know true progress comes with long-term commitments and actions.  We are building a space where our people feel respected for who they are and are rewarded based on the impact they make to the business. 

Regardless of your personal identifiers, at Koa Health you can be yourself, and feel respected, accepted and supported.  We promote an inclusive culture where people who think and act differently can discover ways to learn from each other.  Promoting diversity, inclusion, and equity must be a company-wide effort.  As a scale-up company, we are creating a safe space that fosters acceptance and invites differences as part of our first steps toward building a resilient and inclusive work environment.