Key job responsibilities

Engineer robust, automated reporting systems and dashboards that facilitate data-driven decision making
Partner with Product and Business teams to capture requirements and deliver analytical solutions
Execute targeted data analyses and ensure data quality through regular audits
Create and maintain systems that provide customers with structured, real-time access to their data
Build and maintain business-critical reports across different time horizons (weekly to annual)
Analyze complex historical datasets to uncover trends and present actionable insights through clear communications
Support development teams in building analytics infrastructure for large-scale data analysis and machine learning deployment
Transform data insights into concrete recommendations for business strategy and product development
Develop key performance metrics and create business review presentations using visualization tools
Perform in-depth analysis using advanced SQL and Python programming
Design and maintain data infrastructure, including ETL pipelines and cloud-based solutions
Develop comprehensive documentation and training resources for self-service analytics tools

Basic Qualifications

Bachelor's degree in Computer Science, Engineering, Mathematics, or related field
5+ years of analysing and interpreting data with Redshift, Oracle, NoSQL etc. experience
Experience with data visualisation using Tableau, Quick sight, or similar tools
Experience independently leading and delivering end-to-end analytics analyses and products.
Experience with data modeling, warehousing and building ETL pipelines
Experience in Statistical Analysis packages such as R, SAS and Matlab
Data infrastructure and automation (such as ETL data pipelines, Redshift, S3, Athena, Glue)
Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business

Preferred Qualifications

Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions.
Experience with programming languages such as python, java shell scripts.
Experience with IBM Planning Analytics/TM1 both scripting processes and writing rules.
Experience in Statistical Analysis packages such as R, SAS and Matlab
Experience with design & delivery of formal training curriculum and programs.
Project management, scoping, reporting, and scheduling experience.

Business Intelligence Engineer, DaS FinTech