Sindhuri Bethapudi

Motivated and technically skilled Azure Data Engineer with nearly 4+ years of experience in delivering scalable, secure, and high-performance ETL/ELT solutions across diverse cloud and hybrid environments. Strong background in Databricks, Azure Data Factory, Delta Lake, Synapse, Fabric, and Power BI, with deep expertise in data modelling, Python-based automation, and metadata-driven architecture. Proven record of building and optimizing large-scale data pipelines, ensuring data governance (IAM/RBAC), and driving measurable improvements in data quality and delivery speed.

Known for translating complex business requirements into actionable data strategies, collaborating cross-functionally with stakeholders, and leading automation-focused initiatives. Seasoned BI, Data Analyst & Data Engineer with around 4 years of experience, possessing a comprehensive skill set tailored to effectively manage and optimize data infrastructure including DWH, ETL/ELT, and BI. Proficient in designing and implementing end-to-end ETL solutions using Azure Data Factory, Databricks, Fabric and Synapse Analytics to extract, transform, and load data from various sources into DWH.

Experience on building Data lakes, Medallion Architecture using Azure Data Lake Storage and Azure Blob Storage in which Data lakes are repositories for storing vast amounts of structured and unstructured data. Proficient in design and development of various analytical and interactive self-service dashboards, reports utilising Tableau, Power BI, SSRS and Excel to provide data insights and business insights

BI & Data Engineer - Sun Tech Group

(2024-11 - 2026-03)

Client: Sun Tech Group. Project Duration: Nov 2024 to Mar 2026

• Collaborated with product owners and analysts to gather end-user requirements and KPIs, enhancing delivery accuracy and reducing post-deployment fixes by 35% through proper documentation, data mapping, detailed requirement walkthroughs, and consistent Agile sprint ceremonies and feedback sessions.
• Designed and deployed a greenfield data engineering project using Databricks, Unity Catalog, Microsoft Fabric, and Azure Synapse, creating a robust lakehouse architecture with audit trails, schema evolution support, and scalable architecture for future enhancements and seamless cross-domain data integrations.
• Employed PySpark in Databricks for parallel ETL processing on ADLS-based datasets, reducing pipeline execution time by over 60% while maintaining data integrity, accuracy, and seamless cloud integration.
• Automated data validations, regression testing, and alerts using Python and ADF, significantly improving pipeline reliability, reducing manual QA efforts by 70%, and accelerating data delivery timelines consistently.
• Engineered metadata-driven pipelines using Delta Lake, Azure Purview, and Python, supporting dynamic data ingestion, auditing, lineage capture, and documentation across multiple domains for consistent data governance, ensuring data accuracy, regulatory compliance, and overall operational efficiency.
• Delivered Power BI dashboards linked to Delta Lake layers, allowing business teams to track customer lifecycle metrics, conversion rates, and real-time visuals with a 40% increase in user adoption and engagement through enhanced interactivity and intuitive design features.
• Architected a unified data lake and warehouse model with ADLS and Synapse, balancing real-time and historical data access, improving query performance by 50%, and reducing latency across workloads.
• Implemented fine-grained access control policies using IAM and Unity Catalog, securing 100+ assets while ensuring business teams had role-appropriate access and centralized governance and auditing.
• Developed Python scripts to manage Fabric job triggers, monitoring, and failure recovery, enhancing operational reliability, error traceability, and robust audit logging for compliance needs.
• Integrated CRM/Dataverse data into the Azure ecosystem, enriching customer segmentation efforts, improving marketing insights turnaround by 3x, and enabling highly targeted campaign reporting.
• Developed DevOps pipelines for deploying ADF, notebooks, and security configurations, minimizing manual tasks, improving CI/CD workflows, and achieving 95% consistency across deployment environments.
• Documented and conducted internal training on metadata design, pipeline templating, and RBAC configuration, reducing ramp-up time for new team members by 50% and boosting cross-team efficiency.

BI & Data Engineer - Srijan Technologies Pvt Ltd

(2020-02 - 2023-08)

Client 2: Yamaha, Srijan Technologies Pvt Ltd. Project Duration: July 2022 to August 2023

• Participated in stakeholder interviews to define cross-functional reporting needs across CRM and marketing domains, ensuring requirement clarity and a 25% reduction in revisions, which improved collaboration and minimized project delays significantly through effective communication and documentation.
• Built a comprehensive data platform from scratch using Databricks, Synapse, Unity Catalog, and ADF, improving data accessibility and real-time KPI availability, accelerating data-driven decision-making across multiple business units, and enabling scalable analytics solutions for future growth.
• Developed PySpark pipelines to transform high-volume Cosmos DB and CRM data, reducing data lag from 6 hours to 45 minutes for daily refresh, enabling near real-time analytics for marketing and sales teams.
• Created Python-based utilities for test automation and orchestration, achieving 80%-unit test coverage and early detection of data quality issues, significantly decreasing production defects and improving pipeline reliability through automated validation and monitoring processes.
• Designed a metadata-based ingestion framework that uses Delta Lake, Purview, and Python for ingestion configuration, schema validation, and exception handling, enhancing scalability and maintainability of enterprise-wide data pipelines with improved monitoring and dynamic error handling.
• Built centralized Power BI dashboards on top of curated Delta tables for business KPIs and financial forecasting, decreasing manual reporting time by 60%, and providing executives with actionable, timely insights that enhanced strategic planning and operational efficiency significantly.
• Migrated batch pipelines to Airflow-managed DAGs, improving observability and reducing missed SLAs with alerting and retry mechanisms, increasing overall pipeline robustness and fault tolerance.
• Designed a dual-zone Delta Lake architecture with staging and curated layers, enabling rollback and version tracking while lowering query time by 30%, improving data freshness and audit capabilities.
• Enforced data governance protocols by implementing RBAC roles in Unity Catalog, limiting access by business unit and sensitivity level, ensuring compliance with data privacy regulations across multiple regions.
• Automated CRM-to-Synapse data pipelines using ADF and Python, replacing legacy SSIS jobs and improving ETL performance by 45%, accelerating data availability for reporting and analytics.
• Implemented secure data handoffs to AWS S3 and Redshift for partner analytics, building cross-cloud integration and reducing manual exports by 100%, facilitating seamless data sharing with external stakeholders and improving overall data governance and collaboration efficiency.
• Delivered onboarding documentation, version-controlled notebooks, and reusable YAML-based pipeline templates to reduce development time across future projects, fostering best practices, improving collaboration, and accelerating new team member productivity significantly.

BI & Data Engineer - Srijan Technologies Pvt Ltd

(2021-07 - 2022-05)

Client 3: Enriched web search engine, Srijan Technologies Pvt Ltd. Project Duration: July 2021 to May 2022

• Engaged with functional consultants and business users to gather complex reporting requirements, reducing dependency on legacy BusinessObjects (BO) reports and increasing satisfaction scores by 30%, significantly improving cross-team collaboration and user adoption.
• Implemented a Databricks + Unity Catalog transformation layer, replacing SAP-centric processing with modular, traceable PySpark logic, enhancing maintainability and scalability of data pipelines.
• Rewrote legacy ETL logic from SSIS into PySpark notebooks, achieving an average 65% performance improvement on multi-million-row datasets, enabling faster data refreshes and improved SLA adherence.
• Developed Python test suites integrated into CI pipelines, improving regression coverage and minimizing post-deployment bugs in data flows, reducing manual testing efforts and accelerating release cycles.
• Designed a metadata ingestion framework supporting SAP BW, SSAS, and Azure SQL sources, accelerating onboarding of new data sources by 50%, and standardizing data ingestion and validation processes.
• Created executive-ready Power BI dashboards for sales, finance, and operations, leveraging SAP data and reducing time to insight by 40%, empowering leadership with timely, actionable analytics.
• Set up Delta Lake zones (raw, bronze, silver, gold) with validation and quality scoring layers, improving trust in downstream reporting datasets and facilitating compliance with data governance policies.
• Led the design of a hybrid data lake and warehouse model with SSAS + Synapse on top of ADLS-backed Delta tables, optimizing query performance and supporting both real-time and historical analytics.
• Configured IAM and RBAC policies in Unity Catalog and Synapse, enforcing data masking and audit logging to align with ISO standards, strengthening data security and compliance posture.
• Delivered weekly notebooks and KPI metrics to leadership with integrated Git version control and audit tagging, improving transparency, traceability, and collaborative decision-making processes.
• Integrated SAP BO exports into Delta Lake workflows, enabling dashboard harmonization across Power BI and Tableau for regional teams, facilitating consistent reporting and better business insights.
• Created deployment pipelines in DevOps to automate ARM deployments and parameterized Data Factory integration, reducing manual intervention and accelerating delivery cadence.

BI & Data Engineer - Srijan Technologies Pvt Ltd

(2020-10 - 2021-06)

Client 4: ICTSI, Srijan Technologies Pvt Ltd. Project Duration: October 2020 to June 2021

• Worked with finance and HR teams to finalize detailed requirements for cross-departmental dashboards, leading to a 35% reduction in redundant reporting and improved data consistency across business units.
• Modernized over 50 legacy SSIS packages by adding parameterization and comprehensive error logging, significantly improving pipeline stability and enabling proactive data quality monitoring.
• Designed Power BI and Tableau dashboards focused on operational KPIs and trend analysis, achieving over 70% user adoption and enabling data-driven decision-making across departments.
• Created automated Alteryx workflows to cleanse, transform, and prepare complex SAP data efficiently, improving data availability and reducing pipeline load failures substantially.
• Migrated static SSRS reports to Power BI paginated reports with filter options and scheduled refreshes, replacing multiple manual tasks and streamlining report distribution.
• Developed and maintained SSAS cubes for complex financial data analytics, enabling slicing and dicing across multiple hierarchies and dimensions to support detailed business intelligence reporting.
• Implemented Row-Level Security (RLS) models across Tableau and SSAS platforms to prevent unauthorized data access while maintaining regulatory compliance and data privacy controls.
• Built an intermediate data warehouse layer between SAP and Power BI, significantly improving query response times and reducing data load duplication, enhancing overall report performance.
• Implemented RBAC policies on-premises using Windows Active Directory (AD) and mapped roles into SSAS for secure, scalable role-based report publishing and user access management.
• Coordinated with SAP BW teams to structure BW exports in a reporting-friendly format, ensuring proper joins, accurate hierarchies, and maintained data integrity in Power BI reports.
• Used Tableau Prep and Alteryx Designer to create reusable, parameterized workflows for survey and operational data reporting, increasing processing efficiency and reporting consistency.
• Documented all data pipelines, dashboard KPIs, and governance policies thoroughly, enabling smooth knowledge transfer and reducing dependency on core team members for support.

BI & Data Engineer - Srijan Technologies Pvt Ltd

(2020-02 - 2020-10)

Client 5: Stuff, Srijan Technologies Pvt Ltd. Project Duration: 2020 February to October 2020

• Facilitated requirement gathering sessions with finance and marketing teams to align KPIs and data models, increasing report adoption rate by 35% and improving stakeholder engagement significantly.
• Reengineered existing SSIS packages to optimize data flow and reduce runtime by 40%, effectively handling large data loads from SAP into centralized SQL Server staging environments for reporting.
• Designed end-to-end BI solutions using Tableau and Power BI for campaign and revenue reporting, cutting manual report preparation efforts by 60% and enabling faster business insights.
• Built ETL workflows in Alteryx for rapid prototyping and automating sales and marketing pipelines, leading to a 20% increase in SLA compliance and improved project delivery timelines with increased efficiency.
• Integrated Power BI dashboards with SSAS cubes, enabling faster drilldowns, slicing, and real-time data refreshes for business performance metrics and operational KPIs with enhanced interactivity.
• Developed a central reporting hub using SQL Server Reporting Services (SSRS), streamlining distribution of critical reports and reducing daily email dependency by 70% with automated scheduling.
• Implemented data modelling and governance policies across SSAS and Tableau dashboards in collaboration with business stakeholders, improving platform-wide data consistency and trust significantly.
• Migrated siloed Excel reports to unified Tableau dashboards, enhancing data visualization quality and increasing executive accessibility with a 40% better user satisfaction score overall.
• Established robust data governance controls and user roles using SSAS and SQL Server, ensuring full audit compliance and maintaining secure access control across business departments.
• Improved metadata visibility by integrating Alteryx with SAP metadata, allowing for greater transparency in transformation logic and accurate tracking of enterprise-wide data lineage and dependencies.
• Provided ongoing production support and implemented enhancements for legacy SSIS and Tableau projects, maintaining consistent 99% SLA compliance across all key reporting environments.
• Conducted user training sessions and prepared comprehensive documentation for self-service BI platforms, increasing report generation speed by 3x for non-technical business users.

Bachelor of Technology - Computer Science of Engineering - Jawaharlal Nehru Technological University Kakinada

Master of Science - Data Science - University of East London