We are looking for a Data & Analytics Engineer to join a new, exciting product development at Sambaash, alongside a team of leading domain experts in education & marketing analytics, to create an e-learning analytics application that makes use of AI and ML and enhance our existing cloud based SaaS products. This new product on AWS & Python/Java (just like all other products) is to be integrated with existing learning management systems.
The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data analytics wrangler who enjoys optimizing data systems and building them from the ground up. The Data & Analytics Engineer will support our product managers, software developers, database architects and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.
- Create and maintain optimal data pipeline architecture
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Work with data and analytics experts to strive for greater functionality in our data systems.
We are looking for a candidate with 4 years of experience in a Data / Analytics Engineer role, who has attained a graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
They should also have experience using the following traits / software/tools:
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- A successful history of manipulating, processing and extracting value from large disconnected datasets.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Experience with
○ big data tools: Hadoop, Spark, Kafka, etc.
○ relational SQL and NoSQL databases, including MongDB and Cassandra.
○ AWS cloud services: Lambda, RDS
○ visualizing/presenting data for stakeholders using: AWS QuickSight, Tableau, Power BI
○ analyzing data from 3rd party providers: Google Analytics, Linkedin, Adwords, Facebook Insights, etc.
○ distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, etc.Specific to Project:
- Experience in Amazon AWS data science tooling will be an added advantage
- Must have a good understanding of agile project methodologies adapting SCRUM and Sprint based delivery