Senior Data Engineer - damStack

Overview

About Marseer AI
Marseer AI (www.marseerai.com) is a modular AI activation platform built for DTC and retail e-commerce brands. damStack is Marseer AI's Snowflake-native, dbt-driven data and marketing activation product. It follows a Listen -> Reflect -> React architecture across composable applications, each running inside a customer's own Snowflake data warehouse.

Role Overview
We are looking for a Senior Data Engineer to join the damStack engineering team at Marseer AI. You will design and implement data pipelines, dbt transformation models, and Snowflake-native data products for retail and e-commerce brands. This is a hands-on, high-ownership role across ingestion, transformation, activation workflows, and client onboarding.

What You Will Do

• 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 damStack's Open Schema and unified customer_360 semantic layer.
• Build and refine SQL-based rule engines in Snowflake for priority resolution, frequency capping, and activation orchestration.
• Configure and manage Airbyte connectors for bidirectional data sync such as MongoDB to Snowflake and Snowflake to 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.
• Work directly with client brands to understand data sources, schemas, and business requirements.
• Translate client data into damStack's standardized activity schema and entity resolution framework.
• Troubleshoot data quality and integration issues in client environments.
• Contribute to single-tenant Snowflake deployments, data quality tests, monitors, alerting, and technical design documentation.

Requirements

• 5+ years of professional experience in data engineering.
• Advanced proficiency in dbt Core or Cloud, including incremental models, snapshots, tests, macros, and multi-layer DAG design.
• Strong hands-on Snowflake experience, including DDL/DML, Snowflake Tasks, query optimization, and multi-tenant data architecture.
• Expert-level SQL, including window functions, CTEs, complex joins, and performance tuning.
• Ability to communicate pipeline designs and technical decisions clearly to technical and non-technical stakeholders.

Strongly Preferred

• Experience with Airbyte or comparable ELT / connector platforms.
• Familiarity with Dagster or similar orchestration tools such as Airflow or Prefect.
• Prior experience in a SaaS or data product company shipping reusable, multi-tenant data infrastructure.
• Understanding of identity resolution patterns, surrogate key architectures, customer data platforms, or experimentation / 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.

What We Are Looking For

• Availability for US business hours, with at least 5 hours of overlap with America/New_York.
• Ownership mindset, attention to schema naming, test coverage, documentation, and reliable pipelines.
• Collaborative, structured communication with a distributed team.

What We Offer

• Compensation range: INR 20-30 LPA.
• Fully remote role; work from anywhere in India, with Hyderabad-based candidates preferred.
• High-ownership engineering work on Snowflake, dbt, Airbyte, and Dagster.
• Direct exposure to real DTC and retail e-commerce data problems at scale.
• A small, senior team where your contributions are visible.