Data Engineering Specialist

FEQ327R159 Field Engineering Manager - Specialist Solutions Architects France The Specialist Solutions Architect Manager will lead a team of Specialist Solutions Architects (SSAs) responsible for key elements of the technical sales cycle. You will grow and develop a dynamic team with expertise in areas including enterprise software, data engineering, and data science/machine learning, who will continue to deepen their knowledge of Databricks as the platform expands. You will guide and get involved to enhance your team's effectiveness; be an expert at communicating complex, business value-focused solutions; support complex sales cycles and customer architectures; and build relationships with key stakeholders in large corporations. The SSA Team is engaged in our most important and complex customer engagements, providing deep technical expertise to both new and existing customers. Your team provides specialist expertise to the Solution Architect (SA) and Sales teams, which are responsible for developing and overseeing the overall technical account strategy.  Reporting to the Senior Manager, Field Engineering (Specialist). The impact you will have: * You will hire, train, and grow a diverse team of Specialist Solutions Architects for Databricks, a company in hyper-growth mode * Exceed your region's consumption targets - by working with your cross-functional counterparts to determine where to deploy your team of technical experts to drive the most critical use cases forward * Make your customers extremely successful with Databricks and provide outsized value to their businesses * Establish relationships across the business to make your customers and team successful * Grow Databricks platform usage and prevent churn in strategic accounts by overseeing and retiring a regional growth quota * Create positive morale for the team and help foster a working relationship between Field Engineering, Sales, and other important internal partners * Help resolve customer questions and concerns on accounts and opportunities deemed strategic by Sales and Pre-sales field leadership * Act in a supportive manager capacity, including handling escalations, mentoring team members, building a career path for the assigned team members, etc. What we look for: * Experience in senior roles in the data space with a technical product (i.e. data warehousing, big data, or machine learning) * Experience in leading technical overlay customer-facing teams (team sizes greater than 8), preferably in a pre-sales organisation leading technical engagements * Trusted advisor to technical executives that guide strategic data infrastructure decisions * Team player, but able to challenge and define priorities * Self-starter, challenger, strategic planner & analytical thinker  * Lead a team through best practices for technical qualification, proof of concepts, architecture discussions, and product demonstrations * Experience hiring qualified candidates, ramping them up to be successful, and promoting into larger roles. * Experience working with other teams such as Sales, Product Management, and Professional Services   About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

YOUR MISSION You will be the technical backbone of Armira’s emerging Data & AI function, responsible for building and maintaining the firm’s internal data infrastructure and AI-powered workflows. This is a two-pillar builder role: you will be responsible for (1) designing and implementing Armira’s central data warehouse, ingestion pipelines, data models, and reporting layer, and (2) building AI- and LLM-powered internal tools and workflows that support the investment team’s day-to-day processes, leveraging existing APIs, agent frameworks, and workflow automation tools. Depending on your background, you may lean more toward one pillar initially – what matters is the ability and drive to work across both. YOUR RESPONSIBILITIES Pillar 1: Data Warehouse & Infrastructure * Architect, build, and maintain a centralised data warehouse consolidating fragmented data sources across the firm * Design ETL/ELT pipelines to ingest, transform, and structure data from market databases, deal pipeline sources, and internal systems * Implement data quality frameworks and governance standards appropriate for a regulated financial services environment  * Build dashboards and reporting tools to enable self-service analytics for the investment team   Pillar 2: AI Workflow Development & Internal Tooling * Design and build AI-powered workflows (e.g., LLM integrations, n8n/Make automation) to automate and enhance deal sourcing, due diligence support, and internal reporting workflows * Develop internal tools and applications using LLM APIs, integrating with existing systems (CRM, document management, communication platforms) * Prototype, test, and iterate on AI-powered workflows, translating business requirements into technical solutions under the guidance of senior leadership * Stay current with the rapidly evolving AI/LLM ecosystem and evaluate and recommend new tools and approaches for implementation Technical Approach & Stack Expectations We expect you to leverage well-established, cloud-native tools and to keep the architecture simple, well-documented, and maintainable, so that another engineer could understand and operate key pipelines within a short onboarding period. We are not optimising for cutting-edge custom architectures, but for pragmatic, robust solutions. The expected tech stack aligns with well-established tools in data engineering: * Data Warehouse: e.g., Snowflake, Fabric * Cloud: Preferred Azure * Transformation & Orchestration: dbt / Airflow * Visualisation: Tableau / Power BI * Programming: Python, SQL * AI/LLM: OpenAI, Anthropic APIs; agent frameworks (LangChain, MCP, etc.); workflow automation (n8n, Make) YOUR PROFILE Required Qualifications: * Degree in Computer Science, Data Science, Engineering, or a related quantitative field * 2+ years of professional experience (Specialist: 2–5 years; Manager: 5+ years) in data engineering, software development, or applied data science * Ideally, at least one end-to-end build of a data product, internal tool, or data platform in a professional setting (e.g., designing a data model, building pipelines, and putting dashboards or an internal application into production) * Strong programming skills in Python; solid experience with SQL and modern data stack tools (e.g., Snowflake, dbt, Airflow) * Experience with cloud platforms (AWS, GCP, or Azure) * Familiarity with LLM APIs (OpenAI, Anthropic, or similar) and willingness and experience to build AI-powered workflows (e.g. n8n, make.com) * Ability to work independently, manage ambiguity, and deliver end-to-end solutions * Fluent in English; German proficiency is a strong plus Preferred Qualifications: * Experience in or exposure to financial services, consulting, or private equity * Familiarity with agentic AI frameworks (LangChain, CrewAI, or similar) and/or workflow automation platforms (n8n, Make) * Experience with data visualisation tools (Tableau, Power BI, or similar) * Understanding of PE workflows (deal sourcing, due diligence, reporting) as context for building effective internal tools * Track record of building data products or internal tools in a smaller-team environment WHY US? What We Offer: * Unique opportunity to build a function from scratch at a leading DACH investment holding * Deep exposure to the investment team and PE deal-making: you will sit in on deal discussions, portfolio reviews, and strategy meetings, building a genuine understanding of how private equity works and developing your own professional network in the industry * Competitive compensation  * Munich-based role with work-from-home options, combined with a collaborative, entrepreneurial team culture * High autonomy with clear career growth path as the data function scales * Learning and development budget for conferences, courses, and certifications