- Collaborate with DevOps and Business Intelligence teams to establish a common data processing and analytics platform and best practices.
- Work closely with data scientists and software engineers to support the analysis of data, and the development and validation of models.
- Design and implement data storage solutions to ensure data quality, availability, and scalability.
- Monitor the performance of the data infrastructure and implement optimizations to improve efficiency and reduce costs.
- Participate in technical discussions across the team through code reviews, RFC, or architecture review sessions.
- 2 years of experience working as a data engineer or similar.
- Good understanding of Agile and DevOps practices: version control, CI/CD, Infrastructure-as-Code, containerization, observability/monitoring.
- Experience building data infrastructure to address the needs of business and data teams. Strong knowledge of data architecture, data modeling, and data warehousing.
- Deep familiarity with data processing systems such as Airflow, Dagster, Flyte, Spark, DBT, or similar and data cataloging tools such as Atlas, Amundsen, DataHub, or similar.
- Deep familiarity with SQL (PostgreSQL preferred) and NoSQL databases (Redis, Elasticsearch preferred).
- Experience with AWS's data analytics services and databases, e.g., Redshift, Athena, Glue, EMR, etc. Also, familiarity with data platforms such as Sagemaker, Dataiku, Databricks, Datarobot, or similar.
- Experience with data visualization and reporting tools like Metabase, Tableau, PowerBI, or Looker.
- Hands-on experience supporting high-traffic consumer apps.
- Experience with real-time data processing using Kafka, Flink, or similar tools.
- Data science, MLOps, or related education or work experience
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Senior Consultant - Technology
DID:+65 6727 6129
EA Licence No: 19C9807 | Registration No: R1223789