Responsibilities:
- Expertise in designing and implementing scalable data pipelines (e.g., ETL) and processes.
- Experience building enterprise-scale data warehouse and database models end-to-end.
- Proven hands-on experience with Snowflake and related ETL technologies.
- Experience working with Tableau, Power BI or other BI tools.
- Experience with native AWS technologies for data and analytics such as Redshift, S3, Lambda, Glue, EMR, Kinesis, SNS, CloudWatch, etc.
- Experience with NoSQL databases (MongoDB, Elasticsearch).
- Experience working with relational databases and awareness of writing & optimising SQL queries for analytics and reporting.
- Experience developing scalable data applications and reporting frameworks.
- Experience working with message queues, preferably Kafka and RabbitMQ.
- Ability to write code in Python, Java, Scala or other languages.
Qualification:
- 3+ years experience in architecture of DW/Data Lake solutions for the Enterprise using multiple platforms.
- Experience writing high quality, maintainable SQL on large datasets.
- Expertise in designing and implementing scalable data pipelines (e.g., ETL) and processes in Data Warehouse/Data Lake to support dynamic business demand for data.
- Experience working on building/optimising logical data models and data pipelines while delivering high quality data solutions that are testable and adhere to SLAs.
- Excellent knowledge and experience of query optimisation and tuning.
- Knowledgeable about a variety of strategies for ingesting, modelling, processing, and persisting data.
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