We are looking for a highly responsible and proactive Data Service Engineer to ensure smooth operations across the company’s data ecosystem. This role plays a critical part in monitoring data workflows, resolving operational issues, supporting business users with data-related inquiries, and collaborating across multiple technical and business teams. The ideal candidate is detail-oriented, service-minded, and capable of working in a fast-paced, cross-functional environment.
Key Responsibilities
- Monitor and manage data ingestion and ETL processes from various sources.
- Continuously improve data operational processes and suggest solutions to recurring issues.
- Write SQL queries to extract, validate, and manipulate data from databases.
- Handle incident tickets and coordinate resolution by escalating to relevant domain teams.
- Support business users by assisting with data extraction, validation, and ad hoc requests.
- Investigate and resolve data-related issues or anomalies in collaboration with relevant teams.
- Proactively report daily incidents and operation summaries to the team.
Requirements
- Bachelor’s degree in Computer Science, Information Systems, Statistics, or a related field.
- Strong SQL skills and familiarity with relational databases.
- Solid understanding of data lifecycle, data quality principles, and operational workflows.
- Excellent attention to detail and analytical thinking.
- Ability to communicate effectively with both technical and non-technical teams.
- Self-motivated, with strong problem-solving and time-management skills.
- Experience with ETL/ELT tools such as Azure Data Factory, Airflow, or Databricks.
- Familiarity with cloud platforms (Azure, AWS) and data lakes/warehouses.
- Experience with monitoring or visualization tools (Power BI).
- Knowledge of scripting languages (e.g., Python) for automation or data manipulation.
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