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 DoIdentity 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.
Dentsu also complies with applicable state and local laws regarding employee leave benefits, including, but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act, in accordance with its plans and policies. For further details regarding Dentsu benefits, please visit www.dentsubenefitsplus.com.
Location:USA - Remote - Maryland
Brand:Merkle
Time Type:Full time
Contract Type:Permanent
