Summary
✨ AI‑Generated
An analytics engineering role focused on designing data pipelines, transforming enterprise data, improving data reliability, and enabling advanced analytics through modern technologies.
Highlights
Data engineering role focused on building reliable analytics infrastructure, automation, and AI-ready data assets.
Description
Analytics Engineer – Marketing Data & Salesforce
Job Responsibilities
Design, build, and maintain scalable data pipelines integrating Salesforce, marketing platforms, APIs, and other enterprise data sources.Develop reliable data transformations and models to support analytics, reporting, dashboards, and advanced modeling.Build API-based integrations and Python solutions for automated data ingestion and data processing.Ensure data quality, integrity, and reliability through testing, validation, monitoring, and troubleshooting.Create and maintain data documentation, metadata, definitions, and lineage to support data governance and usability.Develop AI-ready data assets and leverage modern AI tools across development, testing, troubleshooting, and documentation workflows.Qualifications
5+ years of experience in Analytics Engineering, Data Engineering, or a similar role.Strong SQL and Python skills with experience developing production-grade data pipelines.Hands-on experience with a modern cloud data platform such as Snowflake, Databricks, or BigQuery.Experience with REST APIs, data integrations, authentication, pagination, error handling, and schema changes.Extensive experience working with Salesforce data, objects, relationships, and integrations.Strong understanding of marketing data and martech ecosystems, including CRM, campaign, digital, media, and customer data.Experience with data modeling, warehousing, data quality, governance, and downstream analytics.Experience documenting data assets, metadata, lineage, and technical processes.Proficiency with modern AI tools and experience incorporating AI into day-to-day engineering workflows.Preferred
Experience with Rivery and/or Boomi.Experience preparing data and knowledge assets for AI/LLM, RAG, or agent-based applications.Experience with Power BI, Tableau, or Looker.Background in customer identity resolution, marketing attribution, campaign measurement, or complex marketing data models.Experience with data privacy, consent management, and marketing data governance.
