This role will provide data governance and engineering support in various data analytics projects within enterprise financial services clients. This role will assist the leadership in both analysing and formulating the business problems as well as identifying and developing the end-to-end analytics solution, from data capture up to potentials dashboards. The job responsibility is facilitating the wrapping of analytics work into a viable product. The right candidate will be one excited by opportunities to apply advanced analytics techniques to help our clients getting insights from their data using public cloud.
What you'll be responsible for.
- Apply cutting edge technologies and tools in big data and machine learning to build, manage and automate pipelines for data pipelines and analytics platform.
- Build production grade end-to-end analytics solution to solve business challenges together with Data Engineering, Data Scientists and business teams.
- Creation of data governance blueprint and reference architecture for various analytics use cases.
- Study and evaluate the state-of-the-art technologies such as cloud based optimized computing clusters, serverless data processing, and frameworks of data engineering, and establish, apply and maintain best practices and principles of data engineering.
- Perform code reviews to improve the quality of data pipelines
- Monitor and evolve data analytics platforms to support business driven use cases and new consumption patterns.
What you will bring to the role.
- Bachelor’s or Master’s Degree in Software Engineering, Computer Science or related fields
- 5 to 10 years of experience in industry (ideally banking, ecommerce, telecoms, retail, and consulting) with demonstrated track record of leveraging advanced analytics to achieve business impact.
- At least 3 years of experience in data mining and machine learning on large amount of data, and multi-tier software application design
- Excellent understanding of software & data engineering principles and design patterns.
- Familiar with tools such as Anaconda, Jupyter, Eclipse, Jira, Git, SVN, Jenkins, etc
- Great programming skills in Python (Pandas, SciPy, NumPy, PySpark, etc), Scala, Java, SQL, Shell Script
- Experience with traditional data analytics platform stack (Hadoop, Hive, HBase, Spark, Flink, Kafka, Presto, Airflow, etc), and / or cloud (AWS) based analytics services (Amazon Kinesis Data Streams, AWS EMR, AWS Glue etc…) and structured (SQL) and unstructured databases (Graph Database, NoSQL).
- Familiar with industry paradigms and standards for model development, validation and testing and have developed and implemented large-scaled machine learning solutions from end to end.
- Strong in problem-solving, being resourceful with end to end critical thinking to find out solutions even in unfamiliar scenarios.
- Good communication and project management skills.
- Demonstrated strong interests in learning about Data Governance, Analytics & Machine Learning through own initiatives
Sourced offers huge growth opportunities in an innovative, collaborative and inclusive environment. We have regular team social events, individual career development plans, supportive management and team members, training budget to utilise every year, monthly educational workshops, company bonus plans and global relocation packages! We provide opportunities to work on challenging technology solutions, whilst encouraging and aiding the ongoing professional development of our team.
Sourced Group is an equal opportunity employer committed to creating a safe, diverse and inclusive environment. We encourage qualified applicants of all backgrounds including ethnicity, religion, disability status, gender identity, sexual orientation, family status, age, nationality, and education levels to apply. If you are contacted for an interview and require accommodation during the interviewing process, please let us know.