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Senior Data Engineer

2 weeks ago

Singapore Robert Half Full time

**The Company**

Our client is an innovative, international digital insurance consultancy that is growing massively in the region and is looking to hire a Senior Data Engineer. This person will be a key contributor in facilitating projects that involves data engineering expertise to meet their regional business needs. You will collaborate with stakeholders such as senior leaders, developers, data scientists, to architect and develop solutions using a multitude of advanced technologies, tools, and cloud services.

**The Role**

You will develop efficient data pipelines across multiples endpoints that support a variety of data types and formats while following established development and security best practices. You will review existing data architecture and identify issues or opportunities for improvement. You will propose data architecture for new projects. You will work with Event data, unstructured data, and related technology such as NoSQL and document database and establish and maintain platforms, tools, and best practices to improve the overall framework. You will utilize cloud services to improve end-to-end data pipeline performance, availability, and security. You will communicate and work directly with internal stakeholders to develop critical data solutions, make data-driven decisions, and achieve key business goals and partner with the project team to develop reliable, cost-effective, and high-quality solutions and provide timely communications around project progress and issue resolutions. You will also offer mentorship and train peers on standards around data engineering best practices, including documentation.

**Your Profile**

You must possess a Bachelor's degree in Computer Engineering with over 8 years of data engineering experience and at least 2 years of data architecture experience. Solid understanding of SQL and relational databases and data warehouses with good understanding of NoSQL database types and implementations (i.e.. document, key-value, column, graph) are required. Solid experience with modern ELT/ETL tools and frameworks and working with various data types and formats, both structured and unstructured (e.g. JSON, XML, text, Excel, csv, parquet, etc.) are highly desirable. The capability to design, lead, implement, and support data engineering projects, developing and demonstrating proof-of-concept, proficient in at least one cloud technology stack with a focus on services that relate to data engineering, such as Azure (e.g. SQL/PostgreSQL Database, CosmosDB, Blob/Data Lake Storage, DMS, Data Factory, Synapse, Functions, VMs, Container Apps), AWS (e.g. RDS, Aurora, S3, EMR, DynamoDB, DMS, Glue, Athena, Redshift, Lambda, EC2, ECS Fargate are required. Knowledge of managing sensitive data (e.g. PII) and deploying solutions to maintain data privacy and security, experience in Big Data/distributed data processing (e.g. Spark, Hadoop, Flink) and understanding of version control (e.g. GitLab, GitHub, BitBucket) and expertise in at least one programming language (Python preferred, Golang, Scala, Java, etc.) are advantageous.