Data Engineering Azure
Resume:
SREELEKHA KALVA
ETL Developer Data Engineer
*****************@*****.***
LinkedIn Sreelekha Kalva
Professional Summary
6+ years of experience in designing, developing, and supporting complex ETL and data engineering solutions using industry-leading tools such as IBM DataStage (8.x/11.3), SSIS, Informatica PowerCenter, and Azure Data Factory (ADF) across various domains including ϐinance, consulting, and digital marketing.
Proven ability to design and implement scalable, efϐicient, and reusable ETL pipelines, ensuring high performance, low latency, and data integrity in high-volume data environments.
Deep expertise in the full ETL lifecycle from data ingestion and cleansing to transformation, load, and post- load validation using both on-premises and cloud-based architecture.
Proϐicient in SQL (T-SQL, PL/SQL) for advanced data manipulation, joints, indexing strategies, and performance tuning; also skilled in Python scripting using libraries like pandas, NumPy, and matplotlib for automation, data wrangling, and custom data proϐiling.
Developed multiple automation scripts for monitoring, data validation, and error alerting, signiϐicantly reducing manual intervention and downtime.
Hands-on experience working with large datasets stored in Oracle, SQL Server, DB2, and Hive, enabling real-time and batch analytics.
Expertise in migrating legacy ETL jobs from Informatica and COBOL-based systems to modern platforms like DataStage and Azure Data Factory, modernizing data workϐlows.
Experienced in Agile/Scrum environments, participating in daily standups, sprint planning, retrospectives, and working closely with product owners, developers, QA, and DevOps teams.
Strong background in cross-functional collaboration, frequently interfacing with business analysts, solution architects, and stakeholders to align data pipelines with business objectives.
Adept at using Control-M, Azure DevOps, and Git for scheduling, deployment, and version control of ETL artifacts.
Solid knowledge of cloud technologies, including Azure SQL Database, Azure Blob Storage, and Data Lake, with ability to deploy and monitor ADF pipelines across multiple environments.
Skilled in creating and maintaining technical documentation, including source-to-target mapping, data ϐlow diagrams, and deployment guides, to support knowledge sharing and audit readiness.
Recognized for strong troubleshooting skills, with a track record of identifying and resolving complex data and system issues under tight deadlines.
Demonstrates clear, concise written and verbal communication, facilitating smooth collaboration with both technical and non-technical team members.
Awarded multiple internal accolades including “Spot Award” at Deloitte and “Wizard of the Quarter” at Cognizant for outstanding performance and contributions to strategic data initiatives. Technical Skills
ETL Tools: IBM DataStage 8.5/11.3, Informatica PowerCenter 9.1, SSIS, Azure Data Factory (ADF)
Languages & Scripting: SQL (T-SQL, PL/SQL), Python (pandas, NumPy, matplotlib), Shell Scripting
(Unix/Linux)
Databases: Oracle 11g, DB2, SQL Server, Hive
Cloud Platforms: Azure Data Factory, Azure SQL Database, Azure Functions, Azure Blob Storage, Azure DevOps
Big Data Technologies: Hadoop/HDFS, Hive, Azure Data Lake Storage
Platforms: Azure Cloud, Hadoop, Unix/Linux
Scheduling Tools: Control-M, Azure ADF Triggers, Cron Jobs
Version Control & DevOps: Git, Azure DevOps Repos & Pipelines, TFS
Tools & IDEs: Anaconda (Jupyter), DBVisualizer, SSMS, Visual Studio, Putty, WinSC
Reporting & Visualization: Python (matplotlib, seaborn), Power BI (familiarity), Excel
Project Management & Documentation: Jira, Conϐluence, ServiceNow
Methodologies: Agile/Scrum, Waterfall (legacy)
Professional Experience
Deloitte
Senior Analyst Jan 2019 – Apr 2022
Designed and developed Azure Data Factory (ADF) pipelines to automate the ingestion, transformation, and loading (ETL) of structured and unstructured data from resumes to enterprise cognitive search systems.
Built dynamic pipelines using parameterization, integration datasets, and linked services to support scalable deployment across multiple environments.
Collaborated with Azure DevOps teams to deploy ADF solutions via CI/CD pipelines.
Integrated ADF pipelines with Azure Functions and Logic Apps for event-driven execution and error handling.
Developed reusable Python scripts to extract data from web APIs and transform it into analytics dashboards, saving 30+ hours/month in manual reporting efforts.
Automated routine monitoring and data health checks using Python and Control-M scheduler.
Maintained and enhanced SSIS packages for legacy ETL processes, ensuring smooth transition to cloud-native solutions.
Migrated on-premises SSIS workloads to Azure-SSIS Integration Runtime using Lift-and-Shift approach.
Performed extensive SQL-based data validation, reconciliation, and cleansing across multiple data stores
(SQL Server, Oracle, Hive).
Conducted root cause analysis on data anomalies and latency issues, implementing permanent ϐixes through code enhancements and documentation.
Led sprint planning and backlog grooming as part of Agile delivery cycles, coordinating across onshore and offshore delivery teams.
Participated in data governance efforts, ensuring metadata documentation and data quality KPIs were maintained.
Created data mapping documents, functional specs, and technical design documents for internal and client- facing deliverables.
Provided L2/L3 support and coordinated with application and infrastructure teams for issue resolution.
Received “Spot Award” for developing automated test harnesses for ETL jobs, improving defect detection by 40%.
Infosys Limited
Senior Systems Engineer Apr 2018 – Mar 2019
Migrated mainframe-based COBOL ETL logic to IBM DataStage 11.3, reducing dependency on legacy systems.
Designed new DataStage jobs to process daily transaction data from DB2 and Oracle databases.
Built reusable parallel jobs, sequences, and parameter sets to ensure consistency across data workϐlows.
Applied best practices for job design and resource optimization to improve ETL job performance by ~25%.
Implemented robust error handling and logging frameworks using UNIX shell scripts and job-level controls.
Coordinated SIT and UAT phases with business users to ensure data accuracy and completeness.
Developed batch scheduling scripts using Control-M to orchestrate DataStage workloads.
Performed impact analysis and regression testing during change management cycles.
Worked closely with DBA and system admin teams to resolve performance bottlenecks and resource allocation issues.
Developed job control routines using UNIX scripts to manage dynamic parameters and runtime logging.
Engaged in weekly scrum meetings to report blockers, discuss progress, and plan future deliverables.
Created job status dashboards using Python and SQL for business stakeholders.
Authored end-to-end documentation for ETL ϐlows including business logic mapping and job design strategies.
Contributed to knowledge transfer and onboarding sessions for junior developers.
Supported data archival and retention processes in alignment with enterprise data policies. Cognizant Technology Solutions
Programmer Analyst Apr 2016 – Apr 2018
Led the transition from Informatica to IBM DataStage, creating 100+ jobs to replicate and enhance existing data pipelines.
Designed ETL processes to ingest and transform marketing and engagement data from external sources like Google Analytics, LinkedIn, and Facebook Ads.
Developed scalable data warehousing solutions to enable campaign performance reporting and ROI tracking.
Used HDFS and Hive for staging and processing large datasets, enabling analytics for millions of records daily.
Tuned DataStage jobs for improved throughput using partitioning, parallelism, and stage-level optimization.
Integrated ETL ϐlows with Control-M and custom monitoring scripts for automated alerts and execution tracking.
Built reusable data quality rules and validation frameworks for data proϐiling and cleansing.
Authored functional and technical documentation, including data ϐlow diagrams and control tables.
Collaborated with QA teams for test case creation and defect resolution during all SDLC phases.
Developed Informatica mappings before migrating logic to DataStage, ensuring parity through reconciliation scripts.
Partnered with business analysts and SMEs to reϐine requirements and suggest performance- enhancing alternatives.
Supported ad hoc reporting and exploration data analysis requests using SQL and Python (pandas, matplotlib).
Conducted unit and integration testing of ETL jobs, achieving 95% test coverage.
Provided L2 production support and ensured SLA adherence for critical data pipelines.
Received “Wizard of the Quarter” award for delivering high-impact ETL solutions on schedule Education
Bachelor of Engineering in Computer Science
MVSR College of Engineering, Osmania University Aug 2011- June2015 Achievements
“Spot Award” at Deloitte for key contributions to internal data automation tools.
“Wizard of the Quarter” at Cognizant for excellence in ETL development.
“Rising Star” award for impactful performance on enterprise data platform projects. Certiϐication
Azure AI 900
AWS Foundation
Contact this candidate