Senior Data Engineer

We are looking for a Senior Data Engineer to join the damStack engineering team at Marseer AI. You will be a key contributor to the design and implementation of data pipelines, dbt transformation models, and Snowflake-native data products that serve retail and e-commerce brands. This is a hands-on, high-ownership role where you will work across ingestion, transformation, and activation workflows and collaborate directly with client brands on their data onboarding and integration needs.

The candidate will have responsibilities across the following functions:

Data Modelling and Transformation:

• Design, build, and maintain dbt models across staging, intermediate, and mart layers for customer identity, segmentation, journey orchestration, and activation outputs.
• Implement incremental dbt models, snapshots, and tests to ensure data freshness, accuracy, and reliability.
• Contribute to the damStack Open Schema, a registry-driven semantic layer that surfaces a unified customer_360 view to downstream apps.
• Build and refine SQL-based rule engines in Snowflake for priority resolution, frequency capping, and activation orchestration.

Data Pipelines and Integration:

• Configure and manage Airbyte connectors for bidirectional data sync (e. g., MongoDB, Snowflake, Snowflake Klaviyo).
• Build and maintain Dagster pipelines to orchestrate dbt runs, Airbyte sync jobs, and cross-pipeline dependencies.
• Support integration of external marketing platforms into the damStack data layer.

Client Onboarding and Collaboration:

• Work directly with client brands to understand their data sources, schemas, and business requirements.
• Translate client data into damStack's standardised activity schema and entity resolution framework.
• Communicate technical decisions and data pipeline designs clearly to both technical and non-technical stakeholders.
• Troubleshoot and resolve data quality and integration issues in client environments.

Platform Engineering:

• Contribute to damStack's single-tenant deployment model, where each client runs their own isolated Snowflake data warehouse.
• Participate in design reviews and architecture discussions; document decisions using damStack's Engineering Design Document (EDD) conventions.
• Write and maintain data quality tests, monitors, and alerting across the pipeline.

Requirements:

• 5+ years of professional experience in data engineering.
• Advanced proficiency in dbt (Core or Cloud) incremental models, snapshots, tests, macros, and multi-layer DAG design.
• Strong hands-on Snowflake experience, DDL/DML, Snowflake Tasks, query optimisation, and multi-tenant data architecture.
• Expert-level SQL window functions, CTEs, complex joins, and performance tuning.

Strongly Preferred:

• Experience with Airbyte or comparable ELT/connector platforms for bidirectional data sync
• Familiarity with Dagster or similar pipeline orchestration tools (Airflow, Prefect).
• Prior experience in a SaaS or data product company shipping reusable, multi-tenant data infrastructure.
• Understanding of identity resolution patterns, surrogate key architectures, or customer data platforms (CDPs).
• Exposure to experimentation frameworks or A/B testing data pipelines.

Good to Have:

• Familiarity with Klaviyo or other marketing activation / ESP platforms.
• Experience with MongoDB or document-store integrations.
• Prior experience in retail or e-commerce data domains.

Skills

SQL, Snowflake, dbt