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.

Skills

Data Engineering, Data Pipeline, Data Modeling, Data Quality, SQL, Data Validation, Data Observability, Data Visualization, Business Intelligence