Grid Dynamics

Data engineer for advertising and marketing spend

In short

This Data Engineer role involves building data ingestion and transformation pipelines on Azure (Azure Data Factory, Databricks, PySpark, SQL) to consolidate advertising and marketing spend KPIs for a global food and beverage company's reporting initiative. It's an onsite, office-based position in Warsaw with a global consulting/engineering firm, requiring commercial Azure experience and comfort working with evolving requirements and direct business stakeholder communication. Mid-level position requiring at least 2 years of relevant experience.

Description
We are seeking a Data Engineer to join a newly launched business reporting initiative for a global food and beverage leader with a portfolio of widely recognized consumer brands. In this role, you will work between business stakeholders and a diverse landscape of existing reporting tools, connecting multiple data sources, building ingestion and transformation pipelines on Azure, and consolidating advertising and marketing spend KPIs into a single source of truth.
Responsibilities
•Establish connections with each of the existing reporting tools and data sources, choosing the right ingestion approach based on each source's capabilities.
•Design and build data pipelines in Azure Data Factory to bring advertising and marketing expense data onto the platform reliably.
•Process, clean and model data in Databricks using PySpark and SQL to produce consistent, comparable KPIs across sources.
•Consolidate key KPIs into a central "Master" table that serves as the single source of truth for marketing and advertising expense reporting.
•Work closely with business stakeholders to clarify, refine and adapt to evolving requirements as the project takes shape.
Requirements
•Commercial experience as a Data Engineer on the Azure platform.
•Hands-on experience building data processing logic with PySpark and SQL.
•Practical experience designing and orchestrating data pipelines in ADF.
•General understanding of the Azure platform structure, its major services and how they relate to each other.
•Confident communication with business stakeholders and comfort working in a new project where requirements are not yet fixed.
•Ability to ask the right questions, propose solutions and bring structure to ambiguous tasks.
Nice to have
•Experience building CI/CD pipelines for Azure Data Factory.
•Experience setting up DevOps pipelines for Databricks workloads.
Conditions
•Opportunity to work on bleeding-edge projects
•Work with a highly motivated and dedicated team
•Competitive salary
•Flexible schedule
•Benefits package - medical insurance, sports
•Corporate social events
•Professional development opportunities
•Well-equipped office

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