Data Engineer

dentsu Austria

Data Engineer building and maintaining data pipelines for customer data warehouses at Merkle. Develop solutions that enhance customer insights across marketing channels.

Posted 7/1/2026full-timeRemote • Maryland • 🇺🇸 United StatesJuniorMid-Level💰 $40 - $48 per hourWebsite

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheAzureBigQueryCloudETLInformaticaMatillionPythonRDBMSSQLSSIS

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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

Benefits

Comp & perks

Temporary employees are eligible for paid holidays in accordance with dentsu policy
Safe and sick time

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

SQL ProgrammingData ModelingData Quality TestingPython for Data EngineeringRelational Database ManagementData TransformationData Pipeline OrchestrationVersion ControlPerformance TuningData Privacy Practices

Soft Skills

Communication Skills