Director, Data Platform Engineering

SwingDev—a hippo company is the Polish branch of a fast-growing InsurTech product company – Hippo Insurance. They focus on making home insurance smarter and more proactive using technology to bring fresh solutions and create digital products that support customers with impactful results.

• Experience in data engineering, architecture, and data platforms.
• Proven track record of leading technical teams and delivering modern, cloud-based data solutions.
• Experience building data products with real users in mind, managing SLAs, and incorporating continuous feedback loops.
• Hands-on background in semantic layer design and strong analytics engineering practices.
• Knowledge of governance-as-code including data contracts, lineage, quality, and access as core engineering artifacts.
• Working knowledge of AI data infrastructure such as feature stores, vector databases, and pipelines for unstructured data.
• Deep data modeling expertise across multiple paradigms.
• Experience leading teams with diverse skill sets across different geographies.
• Hands-on experience in a director-level role.
• Proficiency in modern data stack including AWS, GCP, Azure, Snowflake, BigQuery.
• Availability to work afternoon hours including occasional evening meetings due to U.S. time zone collaboration.

• Lead a multidisciplinary data organization, hiring, developing, and establishing career frameworks while bridging legacy expertise with modern platform capabilities.
• Collaborate closely with analytics, product, engineering, and business teams to provide the platform foundation they depend on.
• Own the architecture and delivery of the enterprise data platform across cloud environments, supporting batch, streaming, structured, and unstructured data.
• Define and govern enterprise-level data architecture patterns and data modeling standards, applying them pragmatically across domains.
• Develop integration strategies for source systems to enhance data quality, prevent technical debt, and optimize access to reliable data.
• Establish the data product model with clear ownership, SLAs, versioning, and discoverability, shifting the team’s output from pipelines to trusted, consumable data assets.
• Lead the design and build of the enterprise semantic layer with canonical metrics and business definitions that serve BI tooling, AI grounding, and operational consumers from a single source of truth.
• Embed governance in the engineering lifecycle through data contracts, policy-as-code, lineage automation, quality checks, and access controls with auditable versioning.
• Build the data infrastructure required for AI/ML workloads, including feature pipelines, vector stores, embedding pipelines, and model-ready data products across all enterprise data assets.
• Bring experience in data engineering, architecture, and data platforms, along with a track record of leading technical teams and delivering modern, cloud-based data solutions.
• Have built data products with real users in mind, including managing SLAs and incorporating continuous feedback loops.
• Have a hands-on background in semantic layer design and apply strong analytics engineering practices.
• Understand how to implement governance-as-code, including data contracts, lineage, quality, and access as core engineering artifacts.
• Have working knowledge of AI data infrastructure, such as feature stores, vector databases, and pipelines for unstructured data.
• Bring deep data modeling expertise across multiple paradigms and know how to apply the right approach depending on the context.
• Have experience leading teams with diverse skill sets across different geographies, as well as hands-on experience in a director-level role.
• Are proficient in the modern data stack, including cloud platforms (AWS, GCP, Azure), as well as data lakes and data warehouses such as Snowflake or BigQuery, and understand how tooling is evolving to support AI use cases.
• Are available to work in the afternoon hours, including occasional evening meetings due to U.S. time zone collaboration.

Available to work in the afternoon hours including occasional evening meetings due to U.S. time zone collaboration.