Rajkumar Rajagopal

Swedbank AB

Project: Enterprise Analytics Platform (EAP)
Role: Lead Data Engineer

Project Overview

Enterprise Analytics Platform is an enterprise data platform initiative focused on enabling data integration, processing, governance, and analytical capabilities across different data systems.

The engagement involved engineering and enhancing Azure and Databricks-based data platform capabilities, including external data integration, query federation, governance, and data ingestion.

Key Responsibilities and Contributions

Worked on enterprise data engineering solutions using Azure Databricks and Microsoft Azure services.

Designed and developed a custom Query Federation solution to enable data access from Teradata through Databricks before the availability of native Databricks Lakehouse Federation.

Worked with Databricks Unity Catalog for data governance, catalog management, and access control.

Supported data integration and processing using Azure Data Factory, Azure Data Lake Storage, and Azure SQL.

Worked with Azure Key Vault to support secure access to platform credentials and services.

Contributed to Lakeflow-based data ingestion capabilities, including Kafka receiver application integration.

Worked with Hive and Databricks platform components to support enterprise data engineering requirements.

Participated in technical solution design, implementation, troubleshooting, and platform improvements.

Collaborated with engineering and platform stakeholders to deliver integrated data solutions.

Key Technical Highlight

Development of a custom Query Federation capability connecting Teradata and Databricks, enabling cross-platform data access before native Databricks Lakehouse Federation was introduced into the solution.

Technology Stack

Azure Databricks, Azure Data Factory, Azure Data Lake Storage, Azure SQL, SQL Server, Azure Key Vault, Unity Catalog, Hive, Databricks Lakehouse Federation, Lakeflow, Kafka, Teradata.

Ericsson

Project: Data & Analytics Platform
Role: Lead Data Engineer

Project Overview

Enterprise Data & Analytics Platform supporting data ingestion, transformation, processing, and analytical workloads within a large-scale enterprise environment.

The engagement focused on building and supporting modern data engineering capabilities for enterprise data consumers and analytics requirements.

Key Responsibilities and Contributions

Contributed to the design, development, and maintenance of enterprise data engineering solutions.

Developed and supported data ingestion and transformation pipelines for analytical workloads.

Worked with Databricks, Apache Spark, and Delta Lake technologies for distributed data processing.

Supported batch and near-real-time data processing requirements.

Contributed to data platform enhancements, performance improvements, and technical troubleshooting.

Collaborated with engineering teams and stakeholders to understand data requirements and implement technical solutions.

Supported the development of reusable and maintainable data engineering components.

Participated in technical discussions and implementation activities related to enterprise data platform capabilities.

Technology Stack

SAP HANA, Databricks, Apache Spark, Delta Lake, SQL, and related enterprise data platform technologies, Hive, Kafka, Azure Data Factory & Airflow

• Generated detailed studies on potential third-party data handling solutions, verifying compliance with internal needs and stakeholder requirements.
• Designed compliance frameworks for multi-site data warehousing efforts to verify conformity with state and federal data security guidelines.
• Analyzed complex data and identified anomalies, trends and risks to provide useful insights to improve internal controls.
• Developed, implemented and maintained data analytics protocols, standards and documentation.

• Designed compliance frameworks for multi-site data warehousing efforts to verify conformity with state and federal data security guidelines.
• Performed large-scale data conversions for integration into Hadoop based data lake

• Evaluated and improved development work of other developers on team, working to provide training, constructive criticism and knowledge transfer.
• Coordinated efficient large-scale software deployments.
• Documented software development methodologies in technical manuals to be used by IT personnel in future projects.
• Optimized performance through testing and tuning of applications.

• The Velti is now acquired by mGage. I worked with Velti for two different projects like AirTxt and IVR. AirTxt is an old product of Velti.
• Reviewed project specifications and designed technology solutions that met or exceeded performance expectations.
• Worked with software development and testing team members to design and develop robust solutions to meet client requirements for functionality, scalability and performance.
• Analyzed proposed technical solutions based on customer requirements.
• Collaborated with fellow engineers to evaluate software and hardware interfaces.

• Manipulated and implemented object-oriented programming models.
• Collaborated with team to analyze system solutions based on client requirements.
• Documented customer requirements and project plans.
• Discussed project progress with customers, collected feedback on different stages and directly addressed concerns.