Data Engineer - Temporary Worker

This is a temporary position. Employees must be based in the United States and this is a W2 only position.

Role Purpose 

Data Engineers build and operate the modern data platforms behind our clients' customer data warehouses. In this role you will ingest data from diverse sources into cloud data warehouses, rationalize it into a conformed customer data model, engineer customer features, and assemble the unified customer profiles that feed downstream systems — including CDPs, CRMs, and analytics and data science teams. Merkle's solutions enable our clients to better understand and engage their customers and prospects across marketing channels and media. Working within a cross-disciplinary Marketing Technology team, you will develop and maintain scalable, automated, and well-governed data pipelines that turn raw data into reliable customer intelligence. 

Key Responsibilities 

• Contribute to the design of cloud data warehouse architecture and the conformed customer data model 

• Build and maintain SQL transformations, data models, and ELT/data pipelines that ingest, rationalize, and enrich customer data 

• Leverage Merkle's common frameworks, reusable components, and AI-assisted development tools to accelerate delivery 

• Apply development standards, version control, and engineering best practices 

• Engineer customer features and assemble unified customer profiles for downstream CDP, CRM, analytics, and data science consumption 

• Perform development, unit and data-quality testing, and peer code review 

• Automate and orchestrate data pipelines, and manage code from development to production through source control and CI/CD 

• Use AI coding assistants and GenAI tooling responsibly to improve productivity, code quality, and feature development 

Outcomes 

The successful Data Engineer will: 

• Deliver high-quality, well-tested code and design documentation with minimal supervision 

• Be versatile and willing to take on new challenges across different projects and technologies 

• Ship reliable, automated pipelines that meet data-quality and delivery expectations 

• Mentor and provide technical guidance to other developers 

• Maintain a high sense of urgency to deliver on time 

Relationships 

The position interacts regularly with a wide range of internal Merkle teams (including Data Science, Analytics, Quality Assurance, Campaign Management, Business Intelligence, Platform/Information Technology, fellow Developers, and Project Managers) to support the development and ongoing maintenance of the solution. 

• Member of the Development Community  

• Member of designated Capability 

• Member of account/project team(s) 

Key Skills / Experience 

• 2–4+ years building data pipelines and SQL transformations on a major RDBMS and/or cloud data warehouse (e.g., Snowflake, BigQuery, Databricks, Amazon Redshift, Azure Synapse) 

• Strong SQL and database programming skills, including query performance tuning and optimization 

• Hands-on experience with ELT/ETL and data transformation tooling (e.g., dbt, Talend, Informatica, Matillion, SSIS) 

• Strong understanding of relational and dimensional data modeling, and of conformed / customer (Customer 360) data models 

• Proficiency with source control (Git) and branching workflows, plus CI/CD for automated dev-to-prod deployment 

• Understanding of secure data exchange and file management (sFTP, PGP encryption) and of data privacy and governance practices 

• Experience with data pipeline orchestration and automation (e.g., Apache Airflow, Dagster, Prefect, dbt Cloud, Azure Data Factory) 

• Familiarity with software engineering methodologies (Agile/Scrum), issue tracking (Jira), and the full software development lifecycle 

• Understanding of core cloud and IT concepts — compute, storage, networking, and backups 

• Proficiency in Python for data engineering and scripting; comfort with Bash and command-line workflows 

• Solid communication skills, both verbal and written 

• Experience using AI coding assistants (e.g., GitHub Copilot) and a working knowledge of GenAI/LLM concepts 

Preferred Skills 

• Experience with cloud platforms (AWS, GCP, Azure) and infrastructure-as-code (e.g., Terraform) 

• Experience with Customer Data Platforms (CDPs), identity resolution, and database marketing solutions 

• Experience with Business Intelligence tools: Tableau, Power BI, Looker, or MicroStrategy 

• Experience with campaign and engagement tools: Adobe Campaign, Salesforce Marketing Cloud, Braze, Unica, or RedPoint 

• Experience engineering features for machine learning and applying AI/ML to marketing use cases (propensity, segmentation, personalization) 

• Familiarity with data observability, testing, and DataOps practices 

Dentsu 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 ApplicantAccommodations@dentsu.com 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.