Chicago - N. State / Insights & Analysis

Merkle Inc.; Chicago (IL); On-site; USD 94,000 - 135,000; Full time

Benefits offered by this job

Medical, vision, and dental insurance

Disability insurance

Generous paid time off

15+ holidays per year

Paid sick leave

Job summary

Merkle Inc. seeks a Data Engineering Lead to guide and grow high-performing data teams. You will oversee complex data initiatives, shape strategy, and partner with clients to deliver scalable data solutions.

The role blends leadership with hands-on engineering, advancing cloud-native analytics, AI-enabled tools, and governance practices to power modern customer experiences.

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.

Responsibilities

• Lead and grow high-performing data engineering teams through coaching and mentorship.
• Oversee complex data engineering initiatives and guide technical decisions.
• Establish and promote best practices across data engineering (CI/CD, testing, observability, governance).
• Collaborate with clients and stakeholders to translate business goals into engineering solutions.
• Explore AI-enabled tools and cloud-native analytics to modernize data platforms.

Skills

Data engineering experience

Cloud data platforms

SQL

Python

Orchestration tools

Data modeling

Data quality & governance

Git & CI/CD

Leadership experience

Communication skills

Tools

dbt

Apache Airflow

Azure Data Factory

Dagster

Prefect

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.

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.

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,
• Short-term and long-term disability insurance,
• Flexible paid time off,
• At least 15 paid holidays per year,
• Paid sick and safe leave, and

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.