Data Engineering Lead

Dentsu International Americas; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Dentsu International Americas is seeking a Data Engineering Lead to guide teams, shape technical strategy, and partner with clients on scalable data solutions.

You will drive delivery across engagements, define best practices, and lead the adoption of AI-enabled data platforms while ensuring governance and data quality.

Qualifications

• 7+ years in data engineering with cloud-based data platforms and production pipelines.
• Experience with Snowflake, Databricks, BigQuery, Fabric, Synapse, or Redshift.
• Advanced SQL and Python skills.
• Experience with orchestration/transformation tools like dbt, Airflow, ADF, Dagster, Prefect.
• Experience designing data models and customer-centric data solutions.
• Understanding of data quality, lineage, observability, and governance.
• Experience with Git and modern CI/CD workflows.
• 2+ years leading or mentoring data engineering teams.
• Strong communication for both technical and non-technical audiences.

Responsibilities

• Lead and grow high-performing data engineering teams.
• Drive technical delivery across multiple engagements with stakeholder alignment.
• Shape engineering excellence with CI/CD, testing, observability, and governance.
• Partner with clients and stakeholders to translate business goals into engineering solutions.
• Explore AI-enabled data platforms and emerging technologies to modernize data architectures.

Skills

Data Engineering

Leadership

Cloud Platforms

SQL

Python

ETL/ELT

Data Modeling

CI/CD

Observability

Communication

Tools

Snowflake

Databricks

BigQuery

Azure Synapse

Microsoft Fabric

Redshift

dbt

Apache Airflow

Azure Data Factory

Dagster

Prefect

Git

CI/CD

Job description

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...