Join us as we support Singapore’s vision of building a Smart Nation - a nation of possibilities empowered through info-communications technology and related engineering.
The Data Science & Artificial Intelligence Division (DSAID) works with public sector agencies in using data science and AI to improve policy outcomes, service delivery and operational efficiency. We extract data-driven insights and build intelligent platforms to add value to the work of our partner agencies. We also help public sector agencies transform by partnering them in building data science expertise, formulating data strategies and setting up the necessary data infrastructure.
How do we work:
Outcome Driven - Our projects are not academic exercises. We are driven by the “so what” and make sure that our findings and models can be translated into tangible impact.
Start Small and Move Fast - We build things quickly. If it works, good — how can we scale this up further? If not, what went wrong and what can we do better next time?
Ownership - You are not just here to write code, but also to figure out what we should be building and how we should build it.
Continuous Learning - Working on new ideas often means not fully understanding what you are working on. Taking time to learn new architectures, frameworks, technologies, and even languages are not just encouraged but essential.
We are in this Together - We draw from the deep domain knowledge of our partners and best practices from our community of experts.
Read more about us from the team's blog https: //medium.com/dsaid-govtech
We are seeking a Data Engineer to join our Quantitative Strategy team, to be sited with one of our Agency Data Science Teams.
As a Data Engineer, you will be part of a data team deployed at a government agency identified as a strategic partner for DSAID, with the mandate to drive the growth of agency’s data analytics capabilities while operating in close alignment to DSAID's approach and philosophy. Your main role is to build Whole-of-Government data infrastructure at the partner agency, to power insights needed for evidence-based decision-making and enhancing the agency’s service delivery.
This role requires an individual with experience in both on-prem and cloud-based data engineering work, as well as good communication skills, as you will be expected to interact frequently with the partner agency's users to elicit useful business information that enables you to perform your job.
What you will be working on:
- Translate data requirements from business users and data scientists into technical data modelling specifications.
- Interview business users and system owners to elicit information relating to their data infrastructure, data assets, data policies, and use cases.
- Collaborate with partner agency’s IT teams on the following tasks:
- Propose and build ingestion pipelines to collect, clean, harmonise, merge, and consolidate data sources, whether on-prem or in cloud;
- Integrate and collate data sources with data systems;
- Day-to-day monitoring of databases and ETL systems, e.g., database capacity planning and maintenance, monitoring, and performance tuning; diagnose issues and deploy measures to prevent recurrence; ensure maximum database uptime;
- Construct, test, and update useful and reusable data models, with reference to consolidated business insights obtained from users, to serve the data science team and partner agency's needs;
- Propose and implement appropriate cloud data infrastructure in support of the end-to-end analytics deployment lifecycle, taking into account networking between cloud data infrastructure and any on-prem data centres;
- Design and build API gateways to expose data to systems via secure means.
- Research and develop new technologies and approaches for building highly available data persistence systems.
- Advice and support your team on data engineering matters.
- Own and participate in AWS data cloud migration projects (if applicable).
What we are looking for:
- A Bachelor’s Degree, preferably in Computer Science, Software Engineering, Information Technology, or related disciplines.
- Deep understanding of system design, data structure and algorithms, data modelling, data access, and data storage.
- Proficiency in writing SQL for databases such as Postgres, MSSQL, MongoDB, neo4j.
- Demonstrated ability in using cloud technologies such as AWS, Azure, and Google Cloud.
- Experience with data engineering tools and frameworks such as Airflow, Kafka, Hadoop, Spark, Kubernetes.
- Experience in benchmarking, clustering, and tuning the databases for performance, reliability.
- Experience in designing, building, and maintaining batch and real-time data pipelines.
- Experience in automation development, batch, shell, python.
- Familiarity with regular expressions and scripting languages such as bash, korn, awk.
- Familiarity with building and using CI/CD pipelines for platform development.
- Familiarity with DevOps tools such as Docker, Git, Terraform.
- Familiarity with LDAP, OAuth, API gateways.
- Knowledge of IT infrastructure
- Experience with AWS RDS / Spark / other AWS Data Services
- Experience with installation, management, upgrades, backup and restore MSSQL DB
- Working knowledge of SSIS or comparable ETL tools
- Familiarity with government systems and government's policies relating to data governance, data management, data infrastructure, and data security
We are an equal opportunity employer and value diversity at our company as we believe that diversity is meaningful to innovation. Our employee benefits are based on a total rewards approach, offering a holistic and market-competitive suite of perks. This includes generous leave benefits to meet your work-life needs. We trust that you will get the job done wherever you are, and whatever works best for you – so work from home or take a break to exercise if you need to*. We also believe it’s important for you to keep honing your craft in the constantly-evolving tech landscape, so we provide and support a plethora of in-house and external learning and development opportunities all year round.
- Subject to the nature of your job role that might require you to be onsite during fixed hours