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Job Description
Structured overview of role & requirementsAbout This Role
Own and optimise Amazon Redshift data warehouse performance, capacity, and cost, including cluster and table configurations, query performance, and workload management.
Design and implement data aggregation, retention, and provisioning solutions to support reliable, curated datasets and APIs used across product, operations, and external integrator systems.
Develop and maintain robust ingestion and ETL/ELT pipelines with monitoring, data quality checks, reconciliation, and apply AI/automation to enhance engineering workflows and infrastructure monitoring.
Minimum Requirements
Minimum 5 years of hands-on experience with Amazon Redshift focusing on performance tuning, capacity planning, and advanced features like Redshift Spectrum and cross-cluster data sharing.
Strong SQL proficiency, including complex queries and query tuning specific to Redshift/PostgreSQL.
Experience building and maintaining data ingestion and ETL/ELT pipelines, preferably with Python; knowledge of REST API integrations including authentication and rate-limit handling.
Work Experience Required: 5+ years; Notice period: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Deep expertise in managing large-scale Redshift environments with a focus on balancing reliability, scalability, and cost efficiency.
Experience developing end-to-end data solutions including data modelling, roll-ups, backfills, and safe data deletion to support evolving analytical requirements.
Comfortable working in a data engineering team focused on operationalizing data quality, automation, and applying AI-driven optimizations to data pipelines and infrastructure.