DATAECONOMY is one of the fastest-growing Data & Analytics company with global presence. We are well-differentiated and are known for our Thought leadership, out-of-the-box products, cutting-edge solutions, accelerators, innovative use cases, and cost-effective service offerings.
We offer products and solutions in Cloud, Data Engineering, Data Governance, AI/ML, DevOps and Blockchain to large corporates across the globe. Strategic Partners with AWS, Collibra, cloudera, neo4j, DataRobot, Global IDs, tableau, MuleSoft and Talend.
Sr. Tableau Developer/ Lead
Rutherford, NJ
Full-time
Responsibilities:
Collaborate with Business and IT personnel to gather business requirements, perform data analysis to understand to the current data setup and lineage, and recommend the best Tableau BI solutions for the projects.
Help generate insights for designing and developing big data models and solutions to improve data processing efficiency and accuracy.
Help design and develop dashboards, reports, and visualizations using BI tools such as Tableau, Power BI, AbInitio or QlikView, to provide insights on various business performance metrics.
Work with other teams to integrate BI solutions into existing systems to improve data accessibility and data-driven insights.
Provide data lineage, copybook layouts, and data documentation across all applications.
Drive process improvements using data-driven analysis and presenting insights to inform decisions.
Qualifications:
At least 8+ years of experience working in the retail banking domain
Strong experience in big data modeling, data analysis, and Business Intelligence (BI) tools such as Tableau, Power BI or QlikView.
Strong analytical mindset and proficiency in data manipulation using SQL, Excel, and other tools.
Strong written and verbal communication skills, with the ability to communicate complex technical information to non-technical stakeholders.
Experience in working with Agile methodologies and the ability to work in a fast-paced, results-oriented environment.
Experience with workflow modelling would be a plus.