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Senior Analytics Engineer designing and maintaining ELT pipelines and dimensional data models in Google BigQuery using SQL, Python, and dbt to deliver clean datasets to end users.
Builds and maintains scalable data pipelines for wedding planning platforms, using SQL, Python, and dbt to transform complex datasets into actionable insights for business stakeholders.
Designs and builds the runtime infrastructure that powers AI agents, enabling them to safely retrieve, reason over, and act on enterprise data across hundreds of sources with trustworthy, evidence-backed outputs.
Builds and maintains a real-time customer data platform (CDP) called Atlas, focusing on event streaming, identity resolution, and Snowflake/dbt pipelines to unify customer data for media/entertainment insights.
Design and build a scalable, low-latency data platform for a global brokerage infrastructure provider, processing hundreds of millions of events daily using GCP, Kubernetes, and open-source tools.
Lead the design and build of a new data platform from scratch, hiring and managing a team to turn raw data into business insights for marketing, sales, academics, and finance using Snowflake, dbt, and BI tools.
Build and maintain scalable data pipelines on Google Cloud and BigQuery, integrating APIs like Stripe and GA4 to deliver clean, actionable datasets for finance, marketing, and business analytics in a healthcare-focused company.
Build and own end-to-end data pipelines from production databases into a governed lakehouse and Snowflake warehouse, transforming raw data into trusted metrics for analytics, AI, and business teams.
Build and maintain the analytics foundation for a modern travel agency, modeling data and metrics to power AI-driven insights and BI tools for stakeholders.
Build and maintain dbt data models in Snowflake to power analytics and AI across government ERP products, owning pipelines from ingestion to CI/CD deployment.
Data Engineer Location: Remote (UK-based) There may be occasional travel to Manchester or London for events and/or meetings About eComplete eComplete is a specialist growth partner focused on beauty, wellness, and…
The Senior Data Engineer will design, build, and maintain scalable data pipelines and transformations using a code-first approach within a modern data stack. The role focuses on leveraging tools like Snowflake, dbt, and Dagster while integrating AI-assisted development workflows to support the company's data strategy.
Designs and maintains production-grade ELT pipelines in Snowflake, leading data architecture, migration to dbt Cloud, and ensuring data reliability for analytics and reporting in a fast-growing SaaS company.
Builds and maintains scalable data pipelines for migrating/transforming financial data across systems, standardizing schemas, and enabling enterprise visibility into billions of dollars in payments. Core tech: Python/Scala/Java/C#, Databricks/Spark, cloud warehouses, ETL/ELT, and data quality tools.
Liquidline is the fastest-growing commercial coffee solutions provider in the UK and Ireland— not that we're bragging! Our customers are companies that take pride in offering quality refreshments to their employees…
Leads data platform architecture, team development, and analytics industrialization for an edtech company, integrating Salesforce/Moodle and enabling data-driven decisions for marketing, sales, academic, and finance teams using Snowflake/dbt.
Build and maintain data pipelines and BI dashboards to make marketing, sales, and finance data reliable and accessible using Snowflake, Airbyte, dbt Cloud, and Metabase.
Design and optimize scalable data pipelines and transition to a Data Mesh architecture for a betting platform using Spark, Python/Scala, and cloud-native services.
Job Description: ROLE SUMMARY Greenix Pest Control is seeking a Data Warehouse Engineer to own the raw, bronze, and silver layers of our data platform with some duties in gold layer fact and dim modeling, as part of…
Lead Data Engineer responsible for building and evolving the data stack from pipelines to platform, creating infrastructure for product intelligence, financial reporting, and self-serve analytics using technologies like Snowflake, DBT, Airflow, and AWS.
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