Data Engineer

Key Responsibilities

• Design, build, and maintain data pipelines supporting automated campaign management and monitoring.
• Enable data load management and forecasting by processing and aggregating campaign‑related metrics.
• Develop and maintain data models for campaign status, rollout progress, and batch‑level insights.
• Ensure data quality, consistency, and reliability across integrated systems.
• Collaborate with backend and frontend teams to expose analytics‑ready datasets and APIs.
• Support near‑real‑time monitoring and reporting of campaign execution and system behavior.
• Contribute to data observability, documentation, and continuous improvement of data workflows.

Technical Expertise

• Solid experience with data engineering fundamentals and pipeline development.
• Proficiency in SQL and working with structured and semi‑structured data.
• Experience with cloud‑based data platforms and managed data services.
• Familiarity with batch and streaming data processing concepts.
• Experience integrating data from distributed systems and APIs.
• Working knowledge of data validation, monitoring, and performance optimization.

Competencies & Skills

• Strong analytical mindset with the ability to understand complex, domain‑driven data flows.
• Ability to translate business and technical requirements into scalable data solutions.
• Structured approach to data modeling and pipeline design.
• Understanding of how data supports automation, monitoring, and decision‑making.
• Capability to work independently on defined tasks while aligning with the overall data architecture.
• Knowledge of data visualization and BI tools.

Soft skills

• Clear communication with engineers, product managers, and stakeholders.
• Collaborative, team‑oriented working style.
• Ownership mentality for data products and pipelines.
• Curiosity and willingness to continuously improve data solutions.
• Reliability and attention to detail in data‑critical environments.

Nice to have

• Experience with analytics or monitoring use cases in complex platforms.
• Exposure to campaign, rollout, or deployment data.
• Familiarity with event‑driven or near‑real‑time data architectures.
• Interest in large‑scale automation, platforms, or data‑driven operations.