Design and maintain scalable, efficient, and well-partitioned schemas in MSSQL, Redshift, and Snowflake.
Architect and optimize complex queries, stored procedures, indexing strategies, and partitioning for large datasets.
Build, monitor, and maintain data pipelines that ensure timely and accurate delivery of data to internal and external consumers.
Own and enforce data refresh SLAs, ensuring availability, consistency, and reliability across production and reporting environments.
Collaborate with software engineers, analysts, and DevOps teams to ensure data models and queries align with product and reporting requirements.
Proactively identify and remediate performance bottlenecks, slow queries, and data inconsistencies.
Implement and manage database change workflows using schema migration/versioning tools.
Define and promote best practices for data access, security, compliance, and observability.

7+ years of experience in database engineering or backend systems development.
Deep expertise with MySQL, Amazon Redshift, and Snowflake, including schema design and performance optimization.
Design, build, and maintain scalable data pipelines and ETL processes tailored to client needs.
Proven track record maintaining data freshness SLAs and data quality across production pipelines.
Hands-on experience with T-SQL, LinkSQL, query optimization, and indexing strategies.
Experience with query optimization, mapping tables to blocks and partitions, sub-table structure and keying/indexing for efficiency.
Experience of relational data modeling and schema versioning in support of software development.
Experience as the sole or lead database expert on a development team.
Familiarity with source control systems (e.g., Git/Bitbucket) and CI/CD integration.
Strong problem solving skills are desirable.
Transforming product requirements into workable solutions, in collaboration with several development and testing teams.
Writing robust functions, procedures and scripts using SQL.
Being heavily involved in the day to day running of the business dealing with support and performance issues.
Diagnose and troubleshoot data-related issues, providing quick and effective resolutions.
Analyze data workflows and identify areas for improvement, recommending and implementing solutions to optimize performance.
Utilize a proactive approach to foresee potential problems and address them before they impact operations.

Senior AWS Redshift Data Engineer

Key skills