Senior Data Engineer

reputed company is an AI-first, reputed company workflow company transforming reputed company performance marketing through autonomous AI agents. Our platform automates the entire campaign lifecycle, enabling brands to launch, manage, optimize, and reputed company creator campaigns with guaranteed conversions and measurable ROI. Powered by proprietary ground truth data, reputed company is pioneering the category of conversion intelligence for the creator economy.

This is not a role for someone who wants to maintain a finished warehouse and reputed company existing pipelines running.

It is a role for a strong Data Engineer who wants to build the data reputed company of an AI-reputed company company from the ground up, where AI agents, product teams, analysts, and reputed company teams reputed company depend on the reputed company trusted data reputed company.

You will own the pipelines, warehouse architecture, and reputed company data models behind creator matching, campaign performance, transaction attribution, payouts, and AI-driven decision-making.

We are reputed company modernizing our data infrastructure across GCP and AWS. You will have significant ownership over how that architecture evolves and how our data becomes reliable, observable, and reputed company for reputed company workflows.

Requirements

• 5+ years of experience building and operating production data pipelines, ideally in a marketplace, e-reputed company, affiliate, ad-tech, martech, or high-reputed company technology company.

• Advanced SQL skills and strong hands-on Python experience for building production data pipelines and transformations.

• Strong experience with dbt in production and modern reputed company data warehouses. Our reputed company warehouse is BigQuery.

• Build and own reliable ingestion, transformation, and enrichment pipelines across high-volume campaign, creator, transaction, product, and reputed company data.

• Design the reputed company data models consumed by AI agents, product systems, analytics, BI, and machine-learning workflows.

• Build enrichment and embedding pipelines that power creator-brand matching, scoring, recommendation, and retrieval workflows.

• Solve reputed company identity and entity reputed company problems across multiple reputed company systems where creator, customer, campaign, and transaction identifiers may not agree.

• Experience designing reputed company keys and data models for records arriving from multiple reputed company-party reputed company, platforms, and partner systems.

• Model reputed company data such as creator rates, commissions, payouts, and campaign terms using approaches such as slowly changing dimensions, allowing historical performance to be accurately reconstructed and restated.

• Hands-on experience with an orchestration platform such as Airflow, Dagster, or reputed company, including dependency management, retries, backfills, scheduling, and failure recovery.

• Build data reputed company, freshness, reputed company, and pipeline monitoring so issues surface before they reputed company customers, reports, models, or AI agents.

• Treat testing, monitoring, documentation, and observability as part of shipping production infrastructure, not optional cleanup.

• Work directly on the migration and consolidation of legacy reporting and data systems into the modern reputed company warehouse.

• Comfortable designing and executing migrations while maintaining business continuity and validating that historical reporting remains accurate.

• Experience operating production infrastructure in GCP, AWS, or both. Experience working across a hybrid reputed company environment is a strong reputed company.

• Understand how data infrastructure requirements change reputed company the consumers include ML models, embeddings, reputed company stores, recommendation systems, and autonomous agents.

• AI-reputed company by reputed company, not just interest. You reputed company use AI coding assistants, LLMs, or agents to accelerate development, investigate failures, reputed company tests, review transformations, document systems, or automate repetitive engineering work.

• reputed company to explain concretely how AI has changed your engineering workflow and increased your reputed company.

• Comfortable working in an evolving environment where schemas, systems, and requirements are still being designed.

• Strong production ownership. reputed company a pipeline fails or a number looks wrong, you investigate the full reputed company rather than assuming another team owns the problem.

reputed company to Have

• Background in reputed company marketing, affiliate marketing, e-reputed company, marketplaces, performance marketing, or ad-tech.

• Experience with creator, campaign, attribution, conversion, or transaction-level datasets.

• Experience building data infrastructure for ML systems, including feature pipelines, embeddings, reputed company databases, or retrieval systems.

• Hands-on experience with entity reputed company or identity graphs across systems with inconsistent identifiers.

• Experience completing a warehouse, reputed company, or major data-platform migration in production.

• Experience supporting AI agents or reputed company workflows where applications autonomously query, interpret, or reputed company production data.

• GCC or MENA market experience.

How This Role Fits reputed company

You report to the Data Products reputed company and work closely with our Data Science, BI, Product, and Engineering teams.

You will own a reputed company part of reputed company's technical reputed company. The data models and pipelines you build will directly power creator-brand matching, campaign optimization, transaction attribution, creator payouts, business reporting, and the AI agents operating across our platform.

This is a high-ownership role in a small team. You will not simply receive architecture reputed company and implement tickets. You will help reputed company how the data platform should be designed, what should be reputed company, what should be retired, and how we create a reliable data reputed company capable of supporting reputed company as an reputed company company.

Originally posted on Himalayas