Title: Sr. Data Engineer Location: United States time type Full time job requisition id R1124466 Job Description: We’re looking for an Identity Data Engineer who is passionate about data quality, intellectually curious about how real-world identities get resolved, and ready to get deep into the details. You'll work directly with PII-class data at a low level — examining records, interrogating match logic, and developing a genuine understanding of why our matching engines make the decisions they do. Our matching engines link consumer and household identity signals across diverse data sources, combining deterministic logic with increasingly AI-assisted probabilistic resolution. You'll help enhance these engines — improving match rates, reducing false positives, and extending asset coverage. As our AI-augmented matching capabilities grow, so will this role. There is a real long-term track here for an engineer who wants to go deep on identity. What You'll Do Identity Data Engineering - Design, build, and maintain Snowflake-based pipelines that produce and refresh our core consumer and household identity assets on a regular cadence. - Write complex SQL and Python to transform, deduplicate, and enrich identity data at scale — including direct work with PII fields such as names, addresses, emails, and phone numbers. - Investigate data anomalies and quality issues at a record level, tracing match decisions back to source signals and surfacing root causes. - Build and maintain data models that represent consumer and household identity linkage across multiple input sources. Matching Engine Enhancement - Partner with senior engineers and data scientists to enhance our AI-assisted matching engine — contributing to feature design, scoring logic, model evaluation, and threshold tuning. - Implement and test matching algorithm improvements — both AI-driven and rule-based — and measure their real impact on precision, recall, and overall asset quality. - Build evaluation tooling: ground-truth comparisons, match quality dashboards, and regression detection across engine versions. - Help drive the evolution of our matching pipeline toward more intelligent, AI-augmented identity resolution, actively using AI tools as part of your day-to-day engineering workflow. Collaboration & Delivery - Work cross-functionally with Data Science, Product, and downstream engineering teams to translate identity requirements into reliable, scalable solutions. - Participate in code reviews and architectural discussions; apply engineering best practices across the full delivery lifecycle — design, implement, test, and deploy via CI/CD. - Document data models, pipeline logic, and algorithm decisions clearly for both technical and non-technical audiences. - Support QA processes and on-call responsibilities for production identity asset pipelines. - Build automated validation frameworks and quality tracking pipelines that continuously monitor asset health — including data completeness, match consistency, and anomaly detection — and surface results through clear, actionable reporting. What You Bring Required - 4+ years of data engineering or software engineering experience, with a focus on data-intensive systems. - Strong Python skills — you write clean, well-structured code and are comfortable building data processing logic from scratch. - Deep Snowflake fluency: data modeling, complex querying, Streams and Tasks, performance tuning, and preferably Snowpark for Python-native workloads. - Strong SQL fundamentals and comfort working with large, messy, real-world datasets — you know how to interrogate data and know when not to trust it. - Some experience or genuine curiosity around identity matching, deduplication, record linkage, or data quality at scale. - Comfort working with PII-class data responsibly, with awareness of data governance and privacy best practices. - Familiarity with version control (Git), Agile delivery, and CI/CD pipelines. - Comfort applying AI tools in day-to-day engineering work — including prompt engineering, LLM-assisted data processing, and AI-augmented pipeline logic. Nice to Have - Hands-on exposure to matching algorithms — deterministic, probabilistic, or ML/AI-based — and experience evaluating or tuning their performance. - Experience building agentic workflows and working with MCP servers - Some Java experience; comfort with JVM-based tooling is a plus. - Familiarity with consumer or household identity signals: name, address, email, phone, and cross-source linkage. - Cloud experience, preferably AWS; Azure or GCP welcome. - Unix/Bash comfort for scripting and day-to-day environment work. At dentsu, we believe great work happens when we’re connected. Our hybrid way of working combines remote flexibility with regular in-person collaboration to spark ideas and strengthen our teams. Many of our employees who live within commuting distance (90 minutes) from one of our Headquarter or Hub Offices (New York, Chicago, Detroit, Los Angeles) are required to work in the office 2-3 days per week including one Team Day. The minimum number of days may vary by office and role. Dentsu may designate other HQ or Hub offices at any time. Those who do not live near an office may be designated as a remote employee, depending on the role and business needs. Regardless of your work location, we expect you to be flexible to meet the needs of our Company and clients, which may include attendance in an office from time to time. The annual salary range for this position is $94,000 - $152,662. Placement within the salary range is based on a variety of factors, including relevant experience, knowledge, skills, and other factors permitted by law. Benefits available with this position include: - Medical, vision, and dental insurance, - Life insurance, - Short-term and long-term disability insurance, - 401k, - Flexible paid time off, - At least 15 paid holidays per year, - Paid sick and safe leave, and - Paid parental leave. Location: USA - Remote - Maryland Brand: Merkle Time Type: Full time Contract Type: Permanent

• Desenvolver pipelines de dados escaláveis utilizando AWS (S3, EMR, Redshift). • Atuar com processamento de dados em larga escala usando DBT, DuckDB e Spark. • Participar da construção de DAGs dinâmicas via Airflow e YAML. • Discutir requisitos com stakeholders e propor soluções técnicas. • Monitorar e garantir a qualidade dos pipelines e dados processados.

Luxury Presence is building the AI growth platform for real estate. Backed by Bessemer Venture Partners and other top investors, we're a Series C company that has hit $100M in annual recurring revenue. More than 90,000 real estate professionals, including over 30% of the WSJ Real Trends top 100 agents in the United States, use us to run and grow their business. About the Role We’re seeking a Staff Software Engineer to strengthen our real estate MLS data platform squad. You will build robust data pipelines and backend services that power: • High-quality MLS and property data across 400+ feeds • Property discovery and search on agent websites • Personalized listing recommendations and other data-driven features • Conversational and operational AI agents that streamline internal workflows • The evaluation and monitoring infrastructure that keeps these systems improving over time This role sits at the intersection of backend engineering, data infrastructure, and AI-powered products. Who is the Data Platform Squad? We make sure clean, reliable MLS listing records and user click-stream data are always available to our products and customers. Our current team—a mix of data engineers and software engineers—owns the entire listing pipeline: ingestion, transformation, and normalization across 400+ MLS feeds and other sources. We also extend the platform to capture user-activity data for user-facing features such as personalized listing recommendations, and we build AI agents that automate feed onboarding and listing-issue triage, reducing manual effort for internal teams and clients and shortening the path from data to business impact. What You’ll Do Technical leadership & architecture • Own the end-to-end architecture for MLS and property data: streaming and batch pipelines, microservices, storage layers, and APIs • Design and evolve event-driven, Kafka-based data flows that power listing ingestion, enrichment, recommendations, and AI use cases • Drive technical design reviews, set engineering best practices, and make high-quality tradeoffs around reliability, performance, and cost Backend, data & platform engineering • Design, build, and operate backend services (Python or Java) that expose listing, property, and recommendation data via robust APIs and microservices • Implement scalable data processing with Spark or Flink on EMR (or similar), orchestrated via Airflow and running on Kubernetes where applicable • Champion observability (metrics, tracing, logging) and operational excellence (alerting, runbooks, SLOs, on-call participation) for data and backend services Streaming & batch data pipelines • Build and maintain high-volume, schema-evolving streaming and batch pipelines that ingest and normalize MLS and third-party data • Ensure data quality, lineage, and governance are built into the platform from the start—supporting analytics, AI/ML, and customer-facing features • Partner with analytics engineering and data science to make data discoverable and usable (e.g., semantic layers, documentation, self-service tooling) AI agents & data products • Collaborate with ML/AI engineers to design and scale AI agents that automate MLS feed onboarding, listing discrepancy triage, and other operational workflows • Work with frameworks such as PydanticAI, LangChain, or similar to integrate LLM-based agents into our data and service architecture • Help define and implement evaluation, logging, and feedback loops so these agents and data-driven products continuously improve Cross-functional impact & mentorship • Collaborate closely with Product, Engineering, and Operations to shape the roadmap for our data platform, MLS capabilities, and AI-powered experiences • Translate ambiguous business and customer problems into clear technical strategies and phased delivery plans • Mentor and unblock other engineers; elevate the overall level of technical decision-making on the team via pairing, reviews, and design guidance What You’ll Bring Experience & scope • 10+ years of professional software engineering experience, including owning production systems end-to-end • Significant experience working with data-intensive or distributed systems at scale (high volume, high availability) • Prior experience in a senior or staff/lead role where you influenced architecture, standards, and technical direction Core technical skills • Strong programming skills in Python or Java, with experience building microservices and APIs (REST/GraphQL) Hands-on experience with Apache Kafka or similar event/messaging platforms (Kinesis, Pub/Sub, etc.) • Deep experience with: ◦ Spark or Flink for large-scale data processing, across streaming and batch pipelines (on EMR or similar big-data compute) ◦ Airflow (or equivalent orchestration tools) ◦ Kubernetes for running data/compute workloads • Strong SQL and data modeling skills; solid understanding of ETL/ELT patterns, data warehousing concepts, and performance tuning • Experience building on AWS (preferred) or another major cloud provider, with a good grasp of cost, reliability, and security tradeoffs AI agent experience • Experience building or integrating AI agents into production workflows (e.g., internal tools, support automation, operational triage, or data workflows) • Familiarity with frameworks such as PydanticAI, LangGraph, Claude Code or similar, and how they interact with backend services, vector stores, and LLM APIs • Comfort working with logs, telemetry, and evaluation metrics to monitor, debug, and iteratively improve AI-driven systems Leadership & collaboration • Demonstrated ability to lead technical initiatives across teams, from idea to production (alignment, design, implementation, rollout) • Track record of mentoring other engineers and raising the bar on code quality, testing, and design • Strong communication skills; able to clearly explain complex technical decisions to both engineers and non-technical stakeholders • Customer and product mindset: you care about how the data and services you build improve the end-user and client experience, not just the internals Nice to Have • Experience with any of: ◦ Iceberg, Hive, or other table formats/data lake technologies ◦ Snowflake, Athena, Redshift, or other cloud data warehouses ◦ dbt or similar transformation frameworks ◦ Data quality / observability tools (e.g., Great Expectations, Monte Carlo, Datafold) ◦ Vector databases / retrieval (e.g., LanceDB, Pinecone, Elasticsearch/OpenSearch) • Background in real estate, marketplaces, or other domains where data quality and freshness are highly visible to customers • Prior experience in a startup or high-growth environment where you’ve built or significantly evolved a data platform Join us in shaping the future of real estate The real estate industry is in the midst of a seismic shift, and the future belongs to those who break new ground. As one of the fastest-growing companies in the proptech and marketing sectors, Luxury Presence challenges the status quo of what technology can do for real estate agents, leaders, and brokerages. We're a team of agile and tenacious innovators working collaboratively to drive the industry forward. Together, we build game-changing products that empower modern real estate entrepreneurs to dominate their markets. From award-winning web design to agile SEO solutions to cutting-edge AI tools, we deliver tech that anticipates market shifts and keeps our clients ahead of their competition. Founded in 2016 by Stanford Business School alum Malte Kramer, Luxury Presence has grown to a global team ranked on the Inc. 5000 fastest-growing companies list three years in a row. We're backed by world-class investors, including Bessemer Venture Partners, NextEquity Partners, Toba Capital, and Switch Ventures, and have raised $89 million to date. More than 18,000 real estate businesses rely on our platform, including 30% of the Wall Street Journal RealTrends top agents and teams. Additionally, many of the industry's most powerful brokerages rely on Luxury Presence as a trusted business partner. Every year since 2020, Luxury Presence has ranked on BuiltIn's Best Place to Work lists. HousingWire named our founder and CEO a 2024 Tech Trendsetter, we've received several Tech100 Awards, and we just scored an Inman Innovation Award for Best AI-Powered Platform. Luxury Presence is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.

Luxury Presence is building the AI growth platform for real estate. Backed by Bessemer Venture Partners and other top investors, we're a Series C company that has hit $100M in annual recurring revenue. More than 90,000 real estate professionals, including over 30% of the WSJ Real Trends top 100 agents in the United States, use us to run and grow their business. About the Role We’re seeking a Staff Software Engineer to strengthen our real estate MLS data platform squad. You will build robust data pipelines and backend services that power: • High-quality MLS and property data across 400+ feeds • Property discovery and search on agent websites • Personalized listing recommendations and other data-driven features • Conversational and operational AI agents that streamline internal workflows • The evaluation and monitoring infrastructure that keeps these systems improving over time This role sits at the intersection of backend engineering, data infrastructure, and AI-powered products. Who is the Data Platform Squad? We make sure clean, reliable MLS listing records and user click-stream data are always available to our products and customers. Our current team—a mix of data engineers and software engineers—owns the entire listing pipeline: ingestion, transformation, and normalization across 400+ MLS feeds and other sources. We also extend the platform to capture user-activity data for user-facing features such as personalized listing recommendations, and we build AI agents that automate feed onboarding and listing-issue triage, reducing manual effort for internal teams and clients and shortening the path from data to business impact. What You’ll Do Technical leadership & architecture • Own the end-to-end architecture for MLS and property data: streaming and batch pipelines, microservices, storage layers, and APIs • Design and evolve event-driven, Kafka-based data flows that power listing ingestion, enrichment, recommendations, and AI use cases • Drive technical design reviews, set engineering best practices, and make high-quality tradeoffs around reliability, performance, and cost Backend, data & platform engineering • Design, build, and operate backend services (Python or Java) that expose listing, property, and recommendation data via robust APIs and microservices • Implement scalable data processing with Spark or Flink on EMR (or similar), orchestrated via Airflow and running on Kubernetes where applicable • Champion observability (metrics, tracing, logging) and operational excellence (alerting, runbooks, SLOs, on-call participation) for data and backend services Streaming & batch data pipelines • Build and maintain high-volume, schema-evolving streaming and batch pipelines that ingest and normalize MLS and third-party data • Ensure data quality, lineage, and governance are built into the platform from the start—supporting analytics, AI/ML, and customer-facing features • Partner with analytics engineering and data science to make data discoverable and usable (e.g., semantic layers, documentation, self-service tooling) AI agents & data products • Collaborate with ML/AI engineers to design and scale AI agents that automate MLS feed onboarding, listing discrepancy triage, and other operational workflows • Work with frameworks such as PydanticAI, LangChain, or similar to integrate LLM-based agents into our data and service architecture • Help define and implement evaluation, logging, and feedback loops so these agents and data-driven products continuously improve Cross-functional impact & mentorship • Collaborate closely with Product, Engineering, and Operations to shape the roadmap for our data platform, MLS capabilities, and AI-powered experiences • Translate ambiguous business and customer problems into clear technical strategies and phased delivery plans • Mentor and unblock other engineers; elevate the overall level of technical decision-making on the team via pairing, reviews, and design guidance What You’ll Bring Experience & scope • 10+ years of professional software engineering experience, including owning production systems end-to-end • Significant experience working with data-intensive or distributed systems at scale (high volume, high availability) • Prior experience in a senior or staff/lead role where you influenced architecture, standards, and technical direction Core technical skills • Strong programming skills in Python or Java, with experience building microservices and APIs (REST/GraphQL) Hands-on experience with Apache Kafka or similar event/messaging platforms (Kinesis, Pub/Sub, etc.) • Deep experience with: ◦ Spark or Flink for large-scale data processing, across streaming and batch pipelines (on EMR or similar big-data compute) ◦ Airflow (or equivalent orchestration tools) ◦ Kubernetes for running data/compute workloads • Strong SQL and data modeling skills; solid understanding of ETL/ELT patterns, data warehousing concepts, and performance tuning • Experience building on AWS (preferred) or another major cloud provider, with a good grasp of cost, reliability, and security tradeoffs AI agent experience • Experience building or integrating AI agents into production workflows (e.g., internal tools, support automation, operational triage, or data workflows) • Familiarity with frameworks such as PydanticAI, LangGraph, Claude Code or similar, and how they interact with backend services, vector stores, and LLM APIs • Comfort working with logs, telemetry, and evaluation metrics to monitor, debug, and iteratively improve AI-driven systems Leadership & collaboration • Demonstrated ability to lead technical initiatives across teams, from idea to production (alignment, design, implementation, rollout) • Track record of mentoring other engineers and raising the bar on code quality, testing, and design • Strong communication skills; able to clearly explain complex technical decisions to both engineers and non-technical stakeholders • Customer and product mindset: you care about how the data and services you build improve the end-user and client experience, not just the internals Nice to Have • Experience with any of: ◦ Iceberg, Hive, or other table formats/data lake technologies ◦ Snowflake, Athena, Redshift, or other cloud data warehouses ◦ dbt or similar transformation frameworks ◦ Data quality / observability tools (e.g., Great Expectations, Monte Carlo, Datafold) ◦ Vector databases / retrieval (e.g., LanceDB, Pinecone, Elasticsearch/OpenSearch) • Background in real estate, marketplaces, or other domains where data quality and freshness are highly visible to customers • Prior experience in a startup or high-growth environment where you’ve built or significantly evolved a data platform Join us in shaping the future of real estate The real estate industry is in the midst of a seismic shift, and the future belongs to those who break new ground. As one of the fastest-growing companies in the proptech and marketing sectors, Luxury Presence challenges the status quo of what technology can do for real estate agents, leaders, and brokerages. We're a team of agile and tenacious innovators working collaboratively to drive the industry forward. Together, we build game-changing products that empower modern real estate entrepreneurs to dominate their markets. From award-winning web design to agile SEO solutions to cutting-edge AI tools, we deliver tech that anticipates market shifts and keeps our clients ahead of their competition. Founded in 2016 by Stanford Business School alum Malte Kramer, Luxury Presence has grown to a global team ranked on the Inc. 5000 fastest-growing companies list three years in a row. We're backed by world-class investors, including Bessemer Venture Partners, NextEquity Partners, Toba Capital, and Switch Ventures, and have raised $89 million to date. More than 18,000 real estate businesses rely on our platform, including 30% of the Wall Street Journal RealTrends top agents and teams. Additionally, many of the industry's most powerful brokerages rely on Luxury Presence as a trusted business partner. Every year since 2020, Luxury Presence has ranked on BuiltIn's Best Place to Work lists. HousingWire named our founder and CEO a 2024 Tech Trendsetter, we've received several Tech100 Awards, and we just scored an Inman Innovation Award for Best AI-Powered Platform. Luxury Presence is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.