Senior Data Engineer

Role overview

As a Senior Data Engineer, you will be the technical backbone of our client’s data ecosystem, bridging complex data engineering work with strategic business goals. You will partner closely with business stakeholders to understand analytics needs, design robust data transformations, and translate functional and non-functional requirements into clear, actionable engineering documentation.

You will gather, model, and aggregate large datasets, build and optimize high-performance SQL, and improve relational databases and cloud data warehouses. You will also drive data integrity through root-cause analysis across internal and external pipelines, and deliver user-facing reporting and analytics solutions.

Key responsibilities

• Partner directly with business stakeholders to deeply understand analytics needs and pipeline requirements.

• Translate complex stakeholder requirements into practical, detailed technical engineering documentation.

• Assess existing data architectures and define optimal strategies and methodologies for delivering high-value business insights.

• Identify and execute critical data transformations to refine raw data into optimized, production-ready datasets and deliverables.

• Gather, model, and aggregate large and complex datasets that meet functional and non-functional enterprise requirements.

• Design, build, and optimize complex SQL queries and scalable data pipelines for end-user analytics.

• Develop intuitive reports, data visualizations, and interactive dashboards for end users.

• Conduct deep-dive root cause analysis on internal/external data sources and pipeline processes to detect anomalies, resolve issues, and drive continuous performance improvements.

• Design, build, and deploy scalable data warehousing solutions using Snowflake or equivalent modern cloud platforms.

Required qualifications

• Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or equivalent practical experience.

• Advanced SQL & relational databases: Expert-level SQL with daily hands-on experience building complex queries, indexing, and working with relational databases.

• Cloud data warehousing: Proven experience with Snowflake (or an equivalent modern cloud data warehouse).

• Scripting & programming: Advanced proficiency in an object-oriented and/or functional language such as Python, Java, C++, Scala, etc., for data engineering and automation.

• Data visualization & BI tools: Experience building production-grade reports and interactive dashboards in Tableau, Power BI, or similar.

• Analytical & problem-solving skills: Strong ability to perform root-cause analysis across processes and datasets to resolve complex data issues and identify opportunities for optimization.

• Mindset: Fast learner, highly organized, detail-oriented, with strong ownership and a problem-solving drive.