Summary
✨ AI‑Generated
A technology-focused organization is seeking an analytics engineer to design robust data pipelines, transform complex datasets, integrate enterprise systems, and improve data reliability. The role involves Python development, API integrations, documentation, governance, and enabling AI-ready data capabilities.
Highlights
Opportunity to build scalable data solutions, work with modern engineering practices, and create reliable data assets that support analytics and advanced modeling.
Description
Analytics Engineer
We are seeking an Analytics Engineer to build and maintain scalable data pipelines that integrate complex marketing, Salesforce, API, and enterprise data sources.
This role will transform raw data into reliable, well-structured datasets that support analytics, reporting, dashboards, and advanced modeling while leveraging modern AI tools to improve engineering workflows and create AI-ready data assets.
Responsibilities
Design, build, and maintain reliable data pipelines across Salesforce, marketing platforms, APIs, and enterprise data sources.Develop data transformations, models, and integrations that support analytics, reporting, dashboarding, and advanced modeling.Build API-based integrations and Python solutions for automated data ingestion.Ensure data quality, integrity, and availability through testing, validation, monitoring, and troubleshooting.Create and maintain data documentation, metadata, definitions, lineage, and governance standards.Develop AI-ready datasets and documentation to support AI/LLM, RAG, and agent-based use cases.Leverage AI-assisted development tools for engineering, testing, debugging, analysis, and documentation.Qualifications
5+ years of experience in Analytics Engineering, Data Engineering, or a similar role.Strong SQL and Python skills with experience building production-grade data pipelines.Hands-on experience with Salesforce data, including its underlying data structures and relationships.Experience integrating data through REST APIs, including authentication, pagination, error handling, and schema changes.Experience with modern cloud data platforms such as Snowflake, Databricks, or BigQuery.Strong understanding of data modeling, data warehousing, data quality, governance, and pipeline monitoring.Experience working with marketing data and martech ecosystems, including CRM, campaign, digital, media, or customer data.Experience with modern AI tools and incorporating them into day-to-day engineering workflows.Preferred
Experience with Rivery or Boomi for data integration and ingestion.Experience preparing data for AI/LLM applications, including RAG or agent-based solutions.Experience with Power BI, Tableau, or Looker.Background in customer identity resolution, marketing attribution, campaign measurement, or advanced analytics.Experience with data privacy, consent management, and marketing data governance.
