Summary
Overview
Work history
Education
Skills
Certification
References
Timeline
Generic

Venkata Bellam

Coventry,west midlands

Summary

Experienced Data Engineer with over 3 years of hands-on experience in designing, building, and optimizing cloud-based data solutions in fast-paced environments. Proven expertise in developing scalable ETL pipelines using Azure Data Factory, Databricks, and SQL, with a strong focus on data quality, governance, and automation. Known for proactively identifying and resolving data issues, improving pipeline reliability, and enabling real-time reporting through Power BI. Trusted collaborator across engineering and business teams with a flexible, solution-oriented mindset to deliver on project and team goals.

Overview

2
2
years of professional experience
1
1
Certification

Work history

Data engineer

Next plc
Leicester, Leicestershire
01.2024 - Current
  • Designed, developed, and maintained scalable data pipelines in Azure Data Factory (ADF) and Databricks, processing over 5–10 million records daily across retail, warehouse, and digital customer events.
  • Implemented medallion architecture (Bronze–Silver–Gold) using Delta Lake and PySpark to streamline raw-to-curated data transformation and improve auditability and data governance.
  • Built metadata-driven ETL pipelines allowing dynamic source integration and schema evolution without manual code updates, reducing maintenance effort by over 80%.
  • Tuned PySpark jobs in Databricks using partitioning, caching, and broadcast joins—resulting in 60% improvement in performance and reduced compute costs.
  • Enabled high data integrity through data quality rules, exception handling, and layered validation checks, achieving 99.5% data accuracy for business-critical reporting.
  • Built CI/CD pipelines with Azure DevOps, integrating testing, deployment automation, and version control to support Agile delivery cycles.
  • Collaborated with analysts and product owners to translate business logic into SQL and PySpark transformation logic, ensuring KPIs and metrics were correctly calculated and modeled.
  • Supported the Power BI team by delivering clean, curated datasets that enabled near real-time dashboards for sales, returns, stock movement, and event-based insights.
  • Implemented monitoring and alerting via Azure Monitor, ADF logs, and Databricks job metrics to proactively detect failures and reduce downtime by 40%.
  • Participated in code reviews, documentation, and best practice workshops within the data engineering team to establish a centre of excellence mindset.


SQl and BI Developer

Guha Infotech
Milton Keynes, Uk
08.2023 - 06.2024
  • Contributed to the migration of a legacy reporting process, replacing 30+ static SQL scripts with a dynamic stored procedure to automate document generation and improve maintainability.
  • Developed a parameter-driven solution using T-SQL, temporary tables, joins, and ranking functions to handle both net change and full dataset refresh logic.
  • Created and integrated SSIS packages into the main daily ETL process, including audit mechanisms to validate record counts and identify failures during scheduled refreshes.
  • Built SQL views to support SSRS and Power BI reporting, providing structured and reliable access to document-level data for analysis and ad hoc queries.
  • Assisted in the creation of SSRS and Power BI paginated reports, incorporating user-defined parameters to enable flexible filtering and export options.
  • Worked on Power BI dataset development, connecting to multiple data sources and implementing scheduled refreshes to ensure reports remained current for business use.
  • Supported the setup of Power BI Gateways and Workspaces, helping teams publish, schedule, and access reports within defined security scopes.
  • Developed and maintained stored procedures, views, and SQL queries to support reporting logic, with a focus on performance optimization and accuracy.
  • Participated in regular BAU activities, including troubleshooting failed jobs, handling data issues, and responding to stakeholder requests for new metrics or layout changes.
  • Applied SQL tuning techniques to improve stored procedure performance, reducing execution time by 40% on key reporting queries.
  • Documented key processes, transformation logic, and Power BI report structures to ensure maintainability and knowledge transfer across the team.

Data engineer

Tata Technologies
Coventry, united kingdom
06.2023 - 12.2023
  • Designed and delivered end-to-end data engineering solutions on the Azure platform, including ingestion, transformation, and modelling of structured and semi-structured data from diverse client systems.
  • Developed and maintained ETL/ELT pipelines using Azure Data Factory (ADF) and Databricks, enabling clean, timely, and accurate data delivery across automotive, retail, and logistics projects.
  • Built parameterized and reusable pipelines using ADF and dynamic datasets, which reduced redundancy and improved development speed by over 50% across multiple use cases.
  • Created data pipelines to support analytical reporting, feeding data into Power BI dashboards and enabling users to track KPIs such as production efficiency, sales targets, and financial metrics.
  • Implemented data validation logic within ADF data flows and custom PySpark scripts to ensure data integrity, completeness, and schema conformance, achieving >98% data quality on average.
  • Contributed to data lake and data warehouse design, applying dimensional modelling (star and snowflake schemas) to support fast and scalable reporting.
  • Actively supported the migration of on-premises ETL solutions (SSIS) to the Azure cloud, streamlining and modernising legacy data workflows for clients.
  • Participated in Agile delivery cycles, working in cross-functional teams using tools like Azure DevOps, JIRA, and Confluence for task management, documentation, and sprint planning.
  • Introduced CI/CD practices using Git and Azure DevOps to automate deployment of ADF pipelines and Databricks notebooks, improving deployment reliability and traceability.
  • Collaborated closely with business stakeholders to translate data requirements into technical design, ensuring alignment between business goals and data outputs.
  • Documented pipeline designs, transformation logic, and data dictionaries for internal handovers and long-term maintainability.

Education

Master of Science - Computing and Information Systems

University of Greenwich
London

Bachelor of Science - Computer Science

SRM University
India

Skills

Languages & Scripting

  • SQL (T-SQL), Spark(pyspark, spark sql), Python

Data Engineering Tools & Platforms

  • Azure Data Factory (ADF), Databricks, Delta Lake, Azure Synapse, Azure Data Lake Storage Gen2 (ADLS), Microsoft Fabric (Pipelines, Dataflows), SSIS, SSRS, Power BI Service, Power BI Gateway

Data Modeling & Storage

  • Star and Snowflake Schema, Relational Databases (SQL Server, Azure SQL), NoSQL (familiar), Power BI Datasets, Views, Stored Procedures, Temp Tables, CTEs, Dynamic SQL

Big Data & Processing

  • Apache Spark (PySpark), Delta Lake, Medallion Architecture (Bronze, Silver, Gold), REST API Ingestion, Real-time Event Processing, Large-scale Data Ingestion (5–10M rows/day)

Visualization & Reporting

  • Power BI (Dashboards, Paginated Reports, Certified Datasets), SSRS, Excel, KPI Metrics & Ad-hoc Reporting

DevOps & Workflow Automation

  • Azure DevOps (Repos, Pipelines), Git, CI/CD for ADF & Databricks, Monitoring & Logging (Azure Monitor, ADF Alerts), Audit Tables

Concepts & Practices

  • Metadata-Driven ETL, Schema Drift Handling, Data Validation & Quality Assurance, Data Lineage, Data Governance, Row-Level Security (RLS), Parameterized Reporting, Data Warehousing, ETL/ELT Development

Soft Skills & Methodologies

  • Agile Delivery (Scrum, JIRA, Confluence), Stakeholder Communication, Cross-functional Collaboration, Business Analysis Support, Problem Solving, Critical Thinking, Adaptability, BAU & Production Support

Certification

• Microsoft Certified: Azure Data Fundamentals (DP-900)
• Hacker Rank Certified: SQL
• Databricks Certified: Lakehouse Fundamentals

References

References available upon request.

Timeline

Data engineer

Next plc
01.2024 - Current

SQl and BI Developer

Guha Infotech
08.2023 - 06.2024

Data engineer

Tata Technologies
06.2023 - 12.2023

Master of Science - Computing and Information Systems

University of Greenwich

Bachelor of Science - Computer Science

SRM University

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Venkata Bellam