# Data Engineer - MarTech Team
## About the role
We are looking for a Data Engineer to strengthen our MarTech team and help build, maintain and improve the data foundations that support our marketing, customer engagement and growth initiatives.
In this role you work on data pipelines, data models, integrations and automation that support our Customer Data Platform, campaign orchestration, audience activation, personalization and marketing analytics. You work closely with senior engineers, the Tech Lead, Product Owner, Engineering Manager and stakeholders from Marketing, Data, Product and Engineering.
This role is ideal for someone with solid data engineering experience who wants to grow further in a modern MarTech and Growth environment.
## Core Responsibilities
- Design, build and maintain reliable data pipelines for MarTech and Growth use cases
- Work with batch and near-real-time data processing for audience creation, campaign automation, personalization and reporting
- Develop and maintain data models for customer segmentation, marketing activation, attribution and performance analysis
- Collaborate with Tech Lead and senior engineers on architecture and technical design
- Partner with Product, Marketing and Data teams to translate business requirements into data solutions
- Contribute to development and maintenance of integrations with CDP, marketing automation, CRM, analytics and advertising platforms
- Ensure data quality, reliability, observability and performance
- Write clean, maintainable and well-tested SQL and Python code
- Participate in code reviews, technical discussions and incident resolution
- Support privacy, security and compliance requirements, with focus on PII handling, consent and GDPR
- Document data flows, models, assumptions and operational processes
## Tech Stack
- Core Technologies: Databricks (Spark, Delta Lake), Apache Airflow, SQL, Python, dbt, AWS data stack (S3, Redshift, Glue, Lambda, Athena)
- Data Modeling: Dimensional modeling, star schema, customer and event data modeling
- Additional Tools: CDP (Zeotap), Kafka, Kinesis, EventBridge, Looker, Tableau, DataDog, Great Expectations, Terraform, GitHub Actions, CloudFormation
## What we are looking for
- 3–5 years of experience in data engineering
- Strong hands-on experience with SQL and Python
- Experience building and maintaining production-grade data pipelines
- Good understanding of data modeling, ETL/ELT patterns and data quality practices
- Experience with cloud-based data platforms, preferably AWS or Databricks
- Ability to debug data issues and investigate pipeline failures
- Comfortable working with cross-functional teams
- Quality mindset with attention to testing, observability and documentation
- Interest in marketing technology and customer data
- Willingness to learn and take ownership