Job Description:
Lead the Data Teams Powering Modern Customer Experiences
You know great data engineering is about more than pipelines and platforms. It's about helping people make smarter decisions, creating reliable data foundations, and enabling meaningful customer experiences at scale.
As a Data Engineering Lead, you'll guide talented engineering teams, shape technical strategy, partner with clients, and influence how modern data platforms are built and operated. You'll balance leadership with hands-on technical involvement, helping teams solve complex challenges while delivering measurable business outcomes.
This is a true player-coach opportunity where you'll lead people, drive delivery excellence, and help define the future of data engineering, cloud platforms, AI-enabled solutions, and customer data ecosystems.
What You'll Do
Lead and Grow High-Performing Teams
You'll support the development of Data Engineers by providing coaching, mentorship, career guidance, and opportunities for growth. You'll help create an environment where team members can learn, contribute, and thrive.
Drive Technical Delivery
You'll oversee complex data engineering initiatives, partnering with Solution Architects and stakeholders to deliver scalable, high-quality data solutions. You'll help guide technical decisions, manage delivery risks, and ensure successful outcomes across multiple engagements.
Shape Engineering Excellence
You'll establish and promote best practices across data engineering, including CI/CD, testing, code reviews, observability, data quality, documentation, and governance. You'll help create repeatable approaches that enable teams to deliver consistently and effectively.
Partner with Clients and Stakeholders
You'll collaborate with client leaders, business stakeholders, architects, and delivery teams to translate business goals into actionable engineering solutions. You'll communicate complex technical concepts in a way that supports informed decision-making and successful project outcomes.
Innovate with AI and Emerging Technologies
You'll help evaluate and adopt modern technologies, including AI-assisted engineering tools, cloud-native analytics platforms, warehouse-native AI solutions, and next-generation data architecture patterns.
What You'll Bring
Required Qualifications
- 7+ years of experience in data engineering, including cloud-based data platforms, ELT/ETL processes, and production data pipelines.
- Strong experience with platforms such as Snowflake, Databricks, Google BigQuery, Microsoft Fabric, Azure Synapse, or Amazon Redshift.
- Advanced SQL and Python skills.
- Experience with orchestration and transformation tools such as dbt, Apache Airflow, Azure Data Factory, Dagster, Prefect, or similar technologies.
- Experience designing data models and customer-centric data solutions.
- Understanding of data quality, lineage, observability, and governance best practices.
- Experience with Git, CI/CD, and modern engineering workflows.
- 2+ years leading, mentoring, or managing data engineering teams.
- Strong communication skills and the ability to collaborate with technical and non-technical audiences.
Preferred Qualifications
Experience with any combination of the following is welcomed:
- Snowflake, Databricks, dbt, Adobe Real-Time CDP, Salesforce Data Cloud, or related certifications.
- Adobe Experience Platform (AEP), Real-Time CDP, Customer Journey Analytics, Salesforce Data Cloud, Braze, or other customer data platforms.
- AWS, Google Cloud Platform, Microsoft Azure, or Infrastructure as Code technologies such as Terraform.
- AI/ML technologies, warehouse-native AI capabilities, feature engineering, vector databases, or LLM-ready data architectures.
- Data privacy, governance, consent management, and secure data exchange practices.
- Pre-sales, solution design, technical estimation, or consulting experience.
Why You'll Love This Opportunity
Make an Impact Beyond the Code
Your work will influence how organizations use data to better understand and engage their customers. The decisions you help make will drive business outcomes across analytics, customer data platforms, AI solutions, and customer experience technologies.
Grow as a Leader
You'll have the opportunity to mentor engineers, shape engineering culture, build delivery standards, and contribute to the long-term growth of both the team and the broader practice.
Work with Modern Technology
From cloud data warehouses and customer data platforms to AI-assisted engineering and emerging data technologies, you'll have exposure to innovative tools and platforms that are shaping the future of the industry.
We Encourage You to Apply
We recognize that talent comes from many different backgrounds and experiences. If you're excited about leading teams, building modern data solutions, and helping organizations unlock the value of their data, we encourage you to apply, even if your experience doesn't align perfectly with every qualification listed.
Your unique perspective, experience, and ideas can help us build stronger teams, better solutions, and more meaningful outcomes for our clients.
The annual salary range for this position is $94,000 - $135K. 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.
To begin the application process, please click on the “Apply” button at the top of this job posting. Applications will be reviewed on an ongoing basis, and qualified candidates will be contacted for next steps.
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Location:
Chicago - N. StateBrand:
MerkleTime Type:
Full timeContract Type:
PermanentDentsu is committed to providing equal employment opportunities to all applicants and employees. We do this without regard to race, color, national origin, sex , sexual orientation, gender identity, age, pregnancy, childbirth or related medical conditions, ancestry, physical or mental disability, marital status, political affiliation, religious practices and observances, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law.
Dentsu is committed to providing reasonable accommodation to, among others, individuals with disabilities and disabled veterans. If you need an accommodation because of a disability to search and apply for a career opportunity with us, please send an e-mail to [email protected] by clicking on the link to let us know the nature of your accommodation request and your contact information. We are here to support you.
Skills Required
- 7+ years of experience in data engineering, including cloud-based data platforms, ELT/ETL processes, and production data pipelines
- Strong experience with Snowflake, Databricks, Google BigQuery, Microsoft Fabric, Azure Synapse, Amazon Redshift, or similar platforms
- Advanced SQL and Python skills
- Experience with orchestration and transformation tools such as dbt, Apache Airflow, Azure Data Factory, Dagster, or Prefect
- Experience designing data models and customer-centric data solutions
- Understanding of data quality, lineage, observability, and governance best practices
- Experience with Git, CI/CD, and modern engineering workflows
- 2+ years leading, mentoring, or managing data engineering teams
- Strong communication skills and ability to collaborate with technical and non-technical audiences
- Snowflake, Databricks, dbt, Adobe Real-Time CDP, Salesforce Data Cloud, or related certifications
- Experience with Adobe Experience Platform, Real-Time CDP, Customer Journey Analytics, Salesforce Data Cloud, Braze, or other customer data platforms
- Experience with AWS, Google Cloud Platform, Microsoft Azure, or Infrastructure as Code technologies such as Terraform
- Experience with AI/ML technologies, warehouse-native AI, feature engineering, vector databases, or LLM-ready data architectures
- Experience with data privacy, governance, consent management, and secure data exchange practices
- Pre-sales, solution design, technical estimation, or consulting experience
dentsu Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about dentsu and has not been reviewed or approved by dentsu.
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Parental & Family Support — Paid parental leave at full pay and caregiver supports (including backup care) are emphasized as standout elements. Feedback suggests family-oriented benefits are a strong part of the package.
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Leave & Time Off Breadth — Flexible or unlimited PTO, extensive paid holidays, and a year-end office closure are established components. Feedback suggests time-off policies are generous and add meaningful flexibility.
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Retirement Support — A large, established 401(k) plan with employer matching is clearly documented. Feedback suggests retirement benefits feel competitive and straightforward.
dentsu Insights
What We Do
We are dentsu. We team together to help brands predict and plan for disruptive future opportunities and create new paths to growth in the sustainable economy. We know people better than anyone else and we use those insights to connect brand, content, commerce and experience, underpinned by modern creativity. We are the network designed for what’s next









