Role Description As the Lead of the Data Onboarding team, you will serve as a mentor guiding a team of specialists while also executing complex data work yourself. You’ll drive operational excellence through mentorship, project oversight, and hands-on delivery of data onboarding, migration, conversion, and validation projects. This role blends deep technical acumen with thoughtful leadership, and requires a strong understanding of financial portfolio data, AI workflow/agentic AI knowledge, and team enablement. You’ll be instrumental in fostering a collaborative team culture, driving efficiency and quality in our data delivery, and contributing to the growth of both your team and our global data function. Important: - The working schedule for this role is from 6:30 PM to 3:30 AM IST, U.S. business days. - Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position. Qualifications - 4+ years of experience in technology and finance, with exposure to client facing or delivery roles. - Prior experience leading or mentoring others, either formally or informally, with a demonstrated ability to coach, influence, and drive outcomes. - Strong domain knowledge in portfolio, wealth, or investment management and familiarity with financial data structures. - Proficient in SQL/Python and knowledgeable in ETL workflows and data transformation logic. - Strong communication skills, able to convey complex ideas clearly across cultural and functional boundaries. - Highly organized with an eye for detail, able to juggle multiple priorities and deliver under tight timelines. - Solutions driven mindset with a desire to improve and innovate. - Experience working with globally distributed teams and clients is mandatory. Requirements - Responsible for leading the onboarding and implementation of US/LATAM Clients. - Lead and mentor a team of Custodial Data Onboarding Specialists, supporting career development, delivering regular feedback, and helping individuals thrive in their roles. - Manage the team’s work allocation, prioritization, and execution to ensure on time, high quality project delivery. - Provide technical oversight and hands-on contributions to data onboarding, data migration, data conversion, and validation efforts using Databricks, Claude and internal tools. - Establish and maintain standard processes to ensure quality and consistency in client delivery. - Guide the team in issue resolution and escalate blockers proactively, maintaining alignment with internal and client stakeholders. - Collaborate cross functionally across global teams including Sales, Client Solutions, Product, and Engineering to deliver integrated solutions. - Identify and drive opportunities to improve tools, workflows, and automation for greater efficiency. - Foster a team culture that values collaboration, learning, and a shared commitment to client success. Benefits - Addepar is proud to be an equal opportunity employer. - We seek to bring together diverse ideas, experiences, skill sets, perspectives, backgrounds and identities to drive innovative solutions. - We commit to promoting a welcoming environment where inclusion and belonging are held as a shared responsibility. - We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.

• Develop and Maintain Pipelines: build and maintain efficient, scalable data pipelines for use cases such as fraud detection • Support Fraud Analytics: enable analysts and product teams to identify and address emerging fraud patterns through engineered datasets • Integrate Detection Models: collaborate with teams to operationalise external fraud detection models and integrate them into the data infrastructure • Data Storage Optimisation: design and optimise data storage solutions for analysing fraud signals and managing historical data • Feature Engineering: create fraud-specific datasets and features to enhance detection accuracy while supporting business and analytics teams • Pipeline Monitoring and Optimisation: monitor fraud data pipelines to ensure system reliability and troubleshoot performance issues • Best Practices Documentation: establish and document best practices for fraud-related data engineering • Cross-Team Collaboration: partner with data, product, and engineering teams to proactively address fraud trends

Role Description As a Data Engineer , you will be a key player in the end-to-end lifecycle of our large-scale ingestion and transformation engine. You will design, develop, scale, and maintain data pipelines that handle massive data streams, on the order of 100 TB per day. This role offers a dynamic mix of advanced greenfield data engineering and improving the stability and quality of our existing pipelines. What you will do - Design, build, and deploy scalable data pipelines that ingest data from various sources like APIs, Webhooks, and Cloud Storage. - Implement complex domain modeling and transformation logic to unify disparate data sources into high-fidelity data products. - Contribute to architectural improvements by transitioning legacy processes into modern, scalable, and stable data architectures. - Own the support and troubleshooting of live integrations, from diagnosing hotel and internal issues to communicating clearly with stakeholders during incidents. - Drive operational excellence by improving the reliability and quality of our data pipelines through advanced observability, automated testing, and automation. - Collaborate closely with product, engineering, support, and business teams, as well as customers and partners. - Investigate and resolve complex technical issues by performing deep-dive analysis into our code and systems to identify root causes. - Leverage AI and automation to increase engineering velocity, streamline complex debugging, and handle recurring tasks. About our team You will join one of our Integration Engineering teams as a data engineer. Our team's mission is to reliably transform, integrate, and store the vast data sources that power our BI products. We handle a staggering amount of information, processing over 100TB of data daily and managing a dataset with over 3 trillion hotel rates. You'll be part of a highly talented and collaborative group of about 6-8 data engineers, working together to power Lighthouse's core intelligence. Qualifications - Experience building and maintaining production data pipelines, with a growing interest in shaping the architecture around them. - Professional proficiency in Python for large-scale data processing and pipeline development. - Strong knowledge of data cloud technologies and hands-on experience with a major cloud platform like GCP, AWS, or Azure. - Fluent in English with excellent communication skills to discuss technical details and explain complex data flows to technical stakeholders. Requirements - Take pride in the software you build, from initial design to production monitoring and continuous improvement. - Be a forward-thinking builder who uses AI-assisted tools to ship high-quality code faster. Benefits - Flexible time off: Autonomy to manage your work-life balance. - Alan Flex benefits: 160€/month for food or nursery. - Flexible retribution: Optional benefits through tax-free payroll deductions for food, transportation and/or nursery. - Wellbeing support: Subsidized ClassPass subscription. - Comprehensive health insurance: 100% Alan coverage for you, your spouse, and dependents. - Impactful work: Shape products relied on by 85,000+ users worldwide. - Referral bonuses: Earn rewards for bringing in new talent. Technologies you will work with - Python - Google Cloud Platform (GCP) - BigQuery - Spanner - Pub/Sub - Kubernetes - Claude Diversity, equity, inclusion, and belonging Thank you for considering a career with Lighthouse. We are committed to fostering a diverse and inclusive workplace that values equal opportunity for all. We welcome candidates from all backgrounds, regardless of age, gender, race, religion, sexual orientation, and disability. Our commitment to equality is part of our culture. If you require reasonable accommodation at any point during the application or interview process, please notify your recruiter.

Role Description The Data Engineer will focus on designing, developing, and maintaining robust data infrastructure to support use cases such as fraud detection but also general data engineering. The position emphasizes building scalable, high-performing data pipelines and storage systems for fraud use cases. Although this role involves light integration with machine learning models, its primary responsibility is creating the technical foundation that powers such use cases of fraud detection, analytics and reporting. - Develop and Maintain Pipelines: build and maintain efficient, scalable data pipelines for use cases such as fraud detection - Support Fraud Analytics: enable analysts and product teams to identify and address emerging fraud patterns through engineered datasets - Integrate Detection Models: collaborate with teams to operationalise external fraud detection models and integrate them into the data infrastructure - Data Storage Optimisation: design and optimise data storage solutions for analysing fraud signals and managing historical data - Feature Engineering: create fraud-specific datasets and features to enhance detection accuracy while supporting business and analytics teams - Pipeline Monitoring and Optimisation: monitor fraud data pipelines to ensure system reliability and troubleshoot performance issues - Best Practices Documentation: establish and document best practices for fraud-related data engineering - Cross-Team Collaboration: partner with data, product, and engineering teams to proactively address fraud trends Qualifications - 3+ years of experience as a data engineer with some expertise in fraud detection systems or similar - Proficiency in Python and SQL, with knowledge of orchestration and transformation tools (e.g., Apache Airflow, DBT) - Strong knowledge of database design, query optimisation, and ETL/ELT workflows, ideally including relational databases such as MySQL and columnar databases such as ClickHouse - Experience building and maintaining production data pipelines - Familiarity with leveraging machine learning models, primarily as a component of the broader data pipeline, including model registries such as MLflow - Understanding of CI/CD processes for data pipelines - Hands-on experience with data visualization platforms for trend reporting (e.g., Tableau, Superset, Metabase) - Ability to support with model serving components, such as Flask or FastAPI - Familiarity with statistical techniques for fraud trend analysis and reporting - Experience with Git and version control in collaborative workflows Benefits - An annualised rate of €98,000 + retention bonus scheme: Competitive contractor rate with a generous bonus paid every 6 months based on your time with us. - Top-Notch Workstation: We provide the latest MacBook, branded merchandise, and everything you need for an optimal work environment. - Global Co-Working Access: Work from a global network of co-working spaces to keep your work-life dynamic and flexible. - Flexibility: Enjoy full flexibility in work location and hours, supporting a work-life balance tailored to your needs. - Events and Gatherings: Participate in exciting events throughout the year, including team gatherings, cultural events, and other fun activities.