
AVP-Data Visualization
- Bangalore, Karnataka
- Permanent
- Full-time
- Manage data analysis and data integration of disparate systems.
- Create a semantic layer for data virtualization that connects to heterogeneous data repositories.
- Develop reports and dashboards using Tableau, Power BI, or similar BI tools as assigned.
- Assist Data Management Engineering Team (either for Data Pipelines Engineering or Data Service & Data Access Engineering) for ETL or BI Design and other framework related items.
- Work with business users to translate functional specifications into technical designs for implementation and deployment.
- Extract, transform, and load large volumes of structured and unstructured data from various sources into AWS data lakes or modern data platforms like Snowflake.
- Assist with Data Quality Controls as assigned.
- Work with cross functional team members to develop prototypes, produce design artifacts, develop components, perform, and support SIT and UAT testing, triaging and bug fixing.
- Resolve issues and defects in a timely manner and ensure quality deliverables.
- Optimize data integration platform to provide optimal performance under increasing data volumes.
- Develop data integration standards according to the organizations information services policies as well as best practices.
- Conduct review of other integration developers development efforts to ensure consistent methodologies are followed and to make recommendations where necessary.
- Experience working with Agile teams and JIRA.
- Ensure high quality and optimum performance of data integration systems to meet business solutions.
- Bachelors Degree (or foreign equivalent degree) in Information Technology, Information Systems, Computer Science, Software Engineering, or a related field. Experience in the financial services or banking industry is preferred.
- 8+ years of experience with leading design, development, and optimization of dashboards and reports using Power BI, Tableau, and other reporting platforms.
- 5+ years of experience with integration of BI tools with data warehouses / lakes (e.g. Snowflake), along with strong knowledge of Data Modelling, UX/UI for Dashboards.
- 3+ years of experience with migration of reports from legacy platforms.
- 5+ years of experience with data virtualization, data mesh, data fabric, and federated querying platforms such as Denodo, Starburst or OSS platforms are highly desirable.
- 3+ Years of experience working as a Data Engineer, with a focus on building data pipelines and processing large datasets.
- 5+ Years of strong proficiency in AWS services, including AWS Glue, Redshift, EMR, RDS, Kinesis, S3, Athena, DynamoDB, Step Functions and Lambda.
- 2+ Years of Expertise in dealing with data pipelines associated with modern data platforms such as snowflake.
- Solid understanding of data modeling, database design, and ETL principles.
- Experience working with data lakes, data warehouses, and distributed computing systems.
- Familiarity with data governance, data security, and compliance practices in cloud environments.
- Exposure to Data Virtualization tools such as Starburst, Dremio or Denodo is a plus.
- Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
- AWS / Snowflake / Power BI / Tableau certifications are a plus.
- Business Acumen: 15%: Knowledge of Banking & Financial Services Products (such as Loans, Deposits, Forex, etc.). Knowledge of Operational / MIS Reports, Risk and Regulatory Reporting for a US Bank is a plus.
- Data Skills:25%: Must have proficiency in Data Warehousing concepts, Data Lake & Data Mesh concepts, Data Modeling, Databases, Data Governance, Data Security / Protection, and Data Access.
- Tech Skills: 50%: See above
- Human Skills:10%: Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
- BI Tools: Power BI (Desktop, Service), Tableau (Desktop, Server, Online, Prep).
- Data Modelling: Star & Snowflake Schema, Composite Models, RLS, Data Blending
- Cloud Technology: AWS (Redshift, S3, Athena) , Storage S3 Buckets
- Virtualization Layer: Denodo, Dremio, Starburst
- AWS Cloud technology stack (EMR, Redshift, HiveQL, Glue, RDS, etc.)
- Databases: SQL Server , Oracle