Job description

Responsibilities • Develop and optimize data pipelines, ETL/ELT workflows, and data transformations. • Handle complex data integration challenges, crafting solutions that balance performance, scalability, and flexibility. • Take ownership of coding and implementation, ensuring projects are executed efficiently and effectively. • Develop and enforce data quality measures to maintain high levels of integrity and consistency. • Apply critical thinking and non-traditional approaches to improve efficiency and solve data problems in innovative ways. • Challenge conventional solutions when needed, focusing on customized, efficient, and future-proof designs. • Build data solutions that align with business needs, scalability, and long-term growth. • Ensure query performance tuning, indexing, partitioning, and caching strategies are implemented for optimized processing. • Identify and eliminate performance bottlenecks before they impact business users. • Design and maintain data models, warehouses, and integration frameworks that support rapid analytics. • Develop automated monitoring, alerting, and logging to reduce manual oversight. • Implement governance best practices, ensuring security, compliance, and auditability. • Establish and document best practices, workflows, and troubleshooting guides. • Act as a bridge between engineering and analytics, ensuring data is structured and accessible for end-users. • Work alongside Data Modeling Engineers, Analysts, and IT teams to align technical solutions with business objectives. • Take ownership of assigned tasks and ensure projects move forward without direct oversight. Qualifications & Experience • 3-7 years, hands-on experience in data engineering, data pipeline development, or database architecture. • Expert-level SQL skills (Snowflake, SQL Server, etc.), with experience in performance tuning. • Educated to degree level or similar in Computer Science • Strong experience in ETL/ELT development (Azure Data Factory, dbt, Apache Airflow, SSIS, etc.). • Experience working with large-scale data processing, transformation, and storage solutions. • Ability to write clean, efficient, and scalable code for data movement and transformation. • Problem-solving mindset, able to adapt and find unconventional solutions when needed.

Requirements