Analytics Engineering Lead

Databricks

P-1534 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.  As an Engineering Manager, you will work with your team to build mission-critical Lakebase services on the Databricks Platform at scale. Lakebase enables teams to deliver applications faster with an optimized database developer experience, integration with the lakehouse, and simplified operations. It provides a managed Postgres transactional layer for application state and workloads that combine operational data, analytics, and AI. You'll join as one of the founding engineering leaders to build out both the Lakebase product and our London presence.  Key responsibilities include: * Drive continuous delivery within a team of experts in storage technology, distributed systems and Rust. * Manage the development and rollout of storage services that host millions of customer databases across dozens of regions * Partner with peer engineering teams across Databricks to co-evolve Lakebase services with our global infrastructure. * Lead operational excellence in 24/7 operation of our system The impact you will have: * Hire great engineers to build an outstanding team. * Support engineers in their career development by providing clear feedback and develop engineering leaders. * Ensure high technical standards by instituting processes (architecture reviews, testing) and culture (engineering excellence). * Work with engineering and product leadership to build a long-term roadmap. * Coordinate execution and collaborate across teams to unblock cross-cutting projects. What we look for: * Experience with building and shipping storage systems where correctness and performance are essential * BS (or higher) in Computer Science, or a related field * 2+ years of experience building and leading a team of engineers working in a related system * Experience with build, release and deployment infrastructure technologies such as Spinnaker, Jenkins, Airflow, Docker, Kubernetes, Terraform, Bazel, etc. * Ability to attract, hire, and coach engineers who meet the Databricks hiring standards - can up level existing team via hiring top-notch senior talent, growing leaders and helping struggling members; can gain trust of the team and guide their careers * Comfort working on cross-functional projects with the ability to deeply understand product and customer personas 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.

Flo Health

500M+ downloads. 80M+ monthly users. A decade of building – and we’re still accelerating. Flo is the world’s #1 health & fitness app worldwide on a mission to build a better future for female health. Backed by a $200M investment led by General Atlantic, we became the first product of our kind to reach a $1B valuation in 2024 – and we’re not slowing down. With 7M paid subscribers and the highest-rated experience in the App Store’s health category, we’ve spent 10 years earning trust at scale. Now, we’re building the next generation of digital health – AI-powered, privacy-first, clinically backed – to help our users know their body better. The job Flo Health is the world’s most popular women’s health app, supporting over 80 million monthly active users. As our Engineering Manager for the AI Platform, you will lead the core team that builds the shared infrastructure powering every AI feature at Flo—from our chatbot and cycle predictions to personalized health insights.   We don’t just use AI; we build the systems that make it possible at scale. You will work in an environment where we maintain direct technical partnerships with Databricks, OpenAI, Anthropic, and AWS, moving far beyond standard vendor relationships.   The Environment   Our AI Platform team is embedded directly in product delivery, working in cross-functional squads alongside our Data Platform team and external model partners. We operate with a clear but fluid strategy — iterating quickly based on rapid AI/LLM advancements and real-time metrics. You will manage a dynamic environment where roughly 30% of the team's work is reactive, driven by immediate product needs, while maintaining focus on our long-term roadmap.   What You’ll Do * Lead & Empower: Manage a team of senior engineers using a distributed leadership model. You’ll provide the management layer that supports their technical execution, performance, and career growth. * Own the Roadmap: Translate product and company goals into clear team roadmaps, managing the balance between structured delivery and the reactive, business-driven work essential to a platform team. * Drive Delivery: Coordinate cross-pod dependencies, resolve blockers, and track roadmap milestones. * Technical Stewardship: Participate in architectural reviews and provide hands-on technical guidance (~20% of your time). You’ll help the team maintain high standards for safety, medical compliance, and performance. * Cross-Functional Impact: Act as the primary point of contact for stakeholders across Product, Analytics, and Engineering, while representing Flo’s AI vision to our industry partners. What you bring: * Engineering Leadership: Proven track record managing engineering teams in fast-moving product environments. You know how to build high-performing teams, mentor talent, and hire effectively. * AI/ML Infrastructure Depth: You have direct, hands-on experience leading or building ML systems in production. You understand MLOps, model serving, or AI platform engineering. * The "Manager-as-Leader" Mindset: You aren't looking to spend your day coding, but you have the technical depth to participate in architecture discussions and credibly guide technical trade-offs. * Agile & Stakeholder Savvy: You are comfortable operating where priorities shift. You know how to protect roadmap momentum while absorbing urgent requests. * Collaborative Spirit: You thrive in cross-functional setups and understand how to manage diverse teams in an agile environment. Why Join Flo? * Massive Scale: Your work will directly impact millions of users. * Cutting-Edge Tech: Work at the intersection of AI and healthcare, with deep integration into modern LLM stacks and ML infrastructure. * High Visibility: This role offers significant industry exposure, including potential opportunities to present our evaluation platforms at events alongside our technology partners. How we work We’re a mission-led, product-driven team. We move fast, stay focused and take ownership – from brief to build to impact. Debate is encouraged. Decisions are shared. We care about craft, ship with purpose, and always raise the bar. You’ll be working with people who take their work seriously, not themselves. It takes commitment, resilience, and the drive to keep going when things get tough. Because better health outcomes are worth it.  What you'll get We support impact with meaningful reward. Here’s what that looks like: * Competitive salary and annual reviews * Opportunity to participate in Flo’s performance incentive scheme * Paid holiday, sick leave, and female health leave * Enhanced parental leave and pay for maternity, paternity, same-sex and adoptive parents * Accelerated professional growth through world-changing work and learning support * In-person collaboration and work in a hybrid model, with 3 days per week spent in the office * 5-week fully paid sabbatical at 5-year Floversary * Flo Premium for friends & family, plus more health, pension and wellbeing perks Diversity, equity and inclusion Our strength is in our differences. At Flo, hiring is based on merit, skill and what you bring to the role – nothing else. We’re proud to be an equal opportunity employer, and we welcome applicants from all backgrounds, communities and identities. Read our privacy notice for job applicants.

Liberis

Some key info for you about Liberis:  🌱 We were founded in 2007 💰 We have provided over $3bn of funding to small businesses so far 🚀 We have been named in CNBC & Statista Top 150 UK Fintechs for 2025 🌍 We're a global team, with a dynamic presence in 6 key locations around the world 🧠 We're a thriving community of over 290 innovative minds 👩🏾 🤝 👨🏼 We're a vibrant melting pot, celebrating over 27 nationalities in our team 🏢 Our team brings experience from over 740 previous companies, from startups to global giants 🎯 We have just been named as one of FinTech’s Finest 50 by Welcome to the Jungle 💪 We’re proud to be an accredited Real Living Wage employer, ensuring everyone is paid fairly for the great work they do!   Our Product & Engineering Team: Liberis is building the embedded finance platform that lets partners around the world offer innovative funding products to their small business customers. We're a growth-stage fintech with teams in London, Nottingham, Atlanta, Stockholm, Munich and Mumbai, and we’re building a global Product, Data & Engineering team that thrives on autonomy, ownership, and is focused on impact! Our teams solve real-world problems for small businesses, shaping products that unlock opportunity at scale.  Engineering is going through an AI-first transformation, rethinking how teams are structured and how they ship. It's changing what a small team can do! We empower our teams to make decisions, move fast, and take full responsibility for the solutions they deliver. You’ll join a team where curiosity is encouraged and collaboration across Product, Data, Delivery and Engineering is the norm.   About our Data & Insights Team: We exist to build the data platforms and analytics that enable every decision at Liberis to be data-informed—and increasingly, to power AI and ML capabilities across the company! We're building composable, reliable data platforms that scale—from ingesting partner transaction data and event streams, to powering analytics dashboards, to feeding ML models with real-time features. We're also supporting the AI/ML platform team with reliable, low-latency feature pipelines and model serving infrastructure. We're collaborative, pragmatic, and we value moving fast by fixing the right problems—not over-engineering, but building to last!   The team is made up of three functions: Data Platform Engineering: Building and scaling ELT pipelines, managing data infrastructure on GCP, and creating the foundation for analytics and ML feature stores. You'll be part of a small, high-performing team of platform engineers focused on reliability, scale, and developer velocity. Analytics Engineering: Transform raw data into trusted models using DBT and SQL, powering self-serve analytics and business intelligence for stakeholders across the company. Data & Business Intelligence: Build dashboards, partner-facing reports, and insights that drive business decisions and revenue outcomes.   What you'll get to do in the role: * Design, build, and maintain resilient data pipelines that ingest data from Azure SQL, SaaS platforms, and event streams into BigQuery. * Write Python code using DLT to define declarative, testable, version-controlled pipelines - no low-code tools, real engineering. * Build and operate ML feature pipelines - low-latency, real-time data streams that feed ML models with accurate, fresh features. * Own the operational health of systems you build - monitoring, alerting, error handling, and incident response. When the data pipeline goes down, merchant credit decisions and ML model predictions suffer. * Collaborate with analytics engineers to understand data needs, validate schema design, and establish data quality standards that both analytics and ML rely on. * Partner with the AI/ML platform team to design feature stores, streaming feature infrastructure, and model serving pipelines that power Liberis' decisioning engine. * Identify and execute optimisation work - improving performance, reliability, and developer velocity without rearchitecting stable systems. * Mentor junior engineers, helping them grow as engineers and supporting their career development. * Participate in technical decisions about platform direction - infrastructure choices, tooling, architecture trade-offs. * Work cross-functionally with product teams, analytics engineers, BI specialists, and the ML platform team to shape data requirements and platform capabilities.   What we think you'll need: * Proven experience within data engineering roles -building and operating data pipelines at scale * Hands-on experience building Modern Data Stack architectures - you understand the layers: ingestion, warehouse, transformation, orchestration, reverse ETL. You've worked with tools like DLT/Fivetran/Airbyte (ingestion), BigQuery/Snowflake/Redshift (warehouse), DBT (transformation), Airflow/similar (orchestration). * Strong Python programming - you write clean, testable, maintainable code with solid error handling and logging. * Fluent SQL - you can write complex queries, understand execution plans, and optimize for performance and cost. * Experience with cloud data platforms - you've built data warehouses in BigQuery, Redshift, Snowflake, or similar; you understand distributed processing, partitioning, cost optimization, and data governance. * Experience with infrastructure-as-code tools (Terraform, CloudFormation, Pulumi) or equivalent - you version control infrastructure and deploy it via CI/CD pipelines. * Experience working in fast-moving environments where requirements evolve and you adapt quickly without losing sight of reliability. * Understanding of DevOps principles - you think in terms of observability, resilience, incident response, and operational excellence. You can set up monitoring and alerting that actually matters.   Bonus points if you have:  * Experience with DLT or similar declarative ELT frameworks; experience with Google Cloud Platform ecosystem (BigQuery, Cloud Run, Pub/Sub, Dataflow); experience with Kafka, Pub/Sub, or event streaming platforms; experience scaling data systems from 0 to 100M+ events/day; experience implementing data quality frameworks (Great Expectations, dbt tests, custom monitoring); background in fintech or high-stakes data reliability environments where data quality directly impacts revenue. * Experience working with distributed, asynchronous teams across timezones; experience in India tech ecosystem or building in resource-constrained environments; experience migrating from legacy data infrastructure (Azure ADF, traditional ETL) to modern cloud-native stacks.   Career development is really important to us here at Liberis, with progression opportunities for both individual contributors and people managers. You can have a look through our Engineering Career Framework via this link  Our hybrid approach Working together in person helps us move faster, collaborate better, and build a great Liberis culture. Our hybrid working policy requires team members to be in the office at least 3 days a week. At Liberis, we embrace flexibility as a core part of our culture, while also valuing the importance of the time our teams spend together in the office. #LI-FC1