SUMMARY
Do you eat, drink, breathe and speak data? Does crunching data and advising business using data analytics sound exciting to you? Are you enthusiastic about understanding the business and providing data driven insights to improve the bottom line? If so, Rialto has a great role for you!
The Senior Data & Analytics Engineer champions Rialto’s analytics initiatives and executes on providing actionable insights to the business. As part of Rialto’s IT team, the associate will work with businesses in an agile DevOps environment, on Azure cloud. The Senior Data & Analytics Engineer will understand the business context, collect, cleanse, model, analyze data and reach actionable conclusions – using data from both proprietary and third-party data sources. The Senior Data & Analytics Engineer will be responsible for supporting Data & Analytics initiatives for Rialto’s Investment Management & Asset Management business lines. The Senior Data & Analytics Engineer will work in tandem with Business Analysts, Project Managers, Scrum Master and will provide guidance to the Off-shore team, enhancing the value of Rialto’s Information Exchange framework. In addition, the Senior Data & Analytics Engineer will provide feedback to the Director to continually improve the value delivery of the Data & Analytics team to the business and support advanced analytics initiatives for a modern data platform. Note: There will be no people managerial responsibility for this role, and this would be more of a hands-on technical role.
KEY RESPONSIBILITIES
- Collect, assimilate, and build key data sets from various sources that are proprietary, and 3rd party sourced (including public and Government data sources) for both operational and strategic analysis
- Perform exploratory data analysis and identify outlines, basic trends, various quartiles, and understand quality of data
- Orchestrate data pipelines, data transformation jobs, and use generally accepted techniques for massaging, cleansing, wrangling/munching, structuring, enriching, linking of data and identifying common keys
- Execute data analysis on modified data and apply statistical models to solve business challenges
- Understand and explain “How”, “What” and “Why” of business functions using all the data
- Implement New and creative ways of solving business problems using technology: should have a problem-solving and “Hacking” mindset piecing together various data sources to provide data driven business decisions – New and creative ways of solving business problems using technology
- Perform data visualizations, apply Math & Statistics principles, execute Pattern recognition, and apply Domain knowledge
SPECIFICATIONS
- Bachelor’s degree in computer science, data processing or equivalent; or 5 years of experience as data engineer.
- 2+ years of working experience in Python, and DataFrames
- 2+ years of experience with relational database systems (Microsoft SQL Server preferred) and SQL development tools
- 1+ years of familiarity with BI/DW design principles including Star and Snowflake schema, Fact/Dimensional modelling etc.
- 1+ years of data integration tools and methodologies – including APIs, ETL and various methods of connectivity, file transfer and transformations between multiple systems.
- Prior experience with data science concepts such as Regression, Clustering, Classification
- Experience in handling multiple file types: Excel, CSV, JSON, XML
- Strong business acumen and communication skills (written and oral)
ADDITIONAL SKILLS PREFFERED
- Knowledge/Experience of Real estate business, Rent roll analysis, Censuses and population data analysis
- Knowledge/Experience in Financial Services
- Knowledge of Git, Azure cloud
- Knowledge/Experience in Securities and trading
