Data Analyst Senior

Venkata Siva Ram Pande KALIVELA

Senior Data Analyst

Mail: ***************************@*****.*** Phone: +1-940-***-**** Linkedln

PROFESSIONAL SUMMARY:

5+ years of industry experience as a Data Analyst with a solid understanding of Data Modeling, evaluating data sources, and a strong grasp of Data Warehouse/Data Mart design, ETL processes, Business Intelligence (BI), and OLAP applications.

Extensive experience across diverse sectors including finance, retail, healthcare, insurance, and banking, with a passion for tackling challenges and delivering data-driven solutions in any industry and providing strategic insights that support informed business decision-making

Expert in SQL (DDL, DML) with extensive experience optimizing queries and developing complex data scripts across platforms (Oracle, SQL Server, Teradata) to support ETL processes and ensure data accuracy.

Over 3 years of experience in database architecture and ETL pipeline design for large-scale enterprise systems, proficient in leveraging cloud-based solutions (AWS Redshift, Google BigQuery) for efficient, scalable data management and reporting.

Strong experience with Azure Data Factory (ADF) for designing, orchestrating, and automating cloud-based ETL pipelines, alongside familiarity with Azure Synapse, Azure Databricks, and AWS Glue for integrated data analytics.

Expert in Python, with proficiency in libraries such as Pandas, NumPy, Matplotlib, and Seaborn, enabling advanced data analysis and visualization capabilities.

Strong experience in exploratory data analysis to support database development and dashboard creation. Skilled in troubleshooting and resolving data anomalies and data quality issues to ensure seamless operations.

Proficient in data visualization tools such as Power BI, Tableau, Google Looker, and DOMO, with a proven ability to transform raw data into actionable insights through the creation of interactive and intuitive dashboards and reports.

Extensive experience in product and program management across an impactful portfolio of projects and stakeholders, facilitating effective communication and collaboration to achieve strategic business objectives.

Excellent knowledge of the Software Development Life Cycle (SDLC), with practical experience in Agile methodologies (e.g., Scrum, Kanban), enabling effective management of dynamic projects and adaptation to evolving business requirements.

Demonstrated expertise in performing data analysis, data validation, data cleansing, and data variation, with a strong ability to identify and resolve data mismatches across various source systems.

Extensive experience in analyzing large volumes of data across industries such as Finance, Banking, Insurance, and Retail, providing strategic insights that support informed business decision-making.

Skilled in utilizing advanced Excel functions, including VLOOKUP, INDEX MATCH, and other data analysis tools, as well as experience with VBA macros to efficiently retrieve and manipulate complex datasets.

Familiarity with advanced analytical techniques, including Machine Learning (ML) and AI, to enhance data-driven decision-making processes.

Proficient in Apache Airflow for automation and orchestration of data workflows, ensuring efficient data pipeline management and deployment.

Solid understanding of security and privacy principles related to data management and analytics, ensuring compliance with relevant regulations and standards.

An excellent team player with strong communication skills, capable of collaborating with business users, project managers, architects, and peers to maintain a healthy and productive project environment.

Experienced in data governance and measurement best practices, ensuring data quality and accuracy through comprehensive validation techniques and the establishment of consistent frameworks for data management.

TECHNICAL SKILLS:

Data Warehousing & ETL

Informatica 9.1/8.6/7.1.2, SSIS, DataStage 8.x, Azure Data Factory (ADF), AWS Glue, Azure Synapse.

Reporting & BI Tools

Power BI, Tableau, DOMO, Looker, Business Objects 6.5/XIR3, Cognos 8 Suite

Data Modeling

Star-Schema Modeling, Snowflake-Schema Modeling, FACT and Dimension Tables, Erwin, Pivot Tables.

Database Management

Oracle (10g/9i/8i/7.x), MS SQL Server, Teradata, UDB DB2 9.x, MS Access 7.0, AWS Redshift, Snowflake, Google BigQuery, Azure Databricks.

Programming Languages:

SQL (DDL, DML), PL/SQL, T-SQL, Python (Pandas, NumPy, Matplotlib, Seaborn), UNIX Shell Scripting, VB Script, HTML, R

Operating Systems

Windows (95, 98, 2000, NT, XP, Vista), UNIX, Linux Automation & Orchestration: Apache Airflow, CI/CD for Data Pipelines

Machine Learning & AI

Basic Machine Learning using scikit-learn and TensorFlow, along with AI-powered analytics utilizing Azure Machine Learning for enhanced data-driven decision-making.

Testing Tools

WinRunner, LoadRunner, Test Director, Mercury Quality Center, Rational ClearQuest

Other Tools

TOAD, Teradata SQL Assistant, BTEQ, MS Office Suite (Word, Excel, Project, Outlook), Microsoft Fabric

PROFESSIONAL EXPERIENCE:

Client: Santander Consumer USA Texas, USA. Nov 2023 - Present

Role: Sr Data Analyst

Desciption: Santander Consumer USA is a leading consumer finance company that offers a range of financial products and services, primarily focused on automotive lending. They provide financing options for new and used vehicles, as well as other consumer loans. Santander Consumer USA is part of the broader Santander Group, a global banking and financial services institution.

Responsibilities:

Analyze functional and non-functional data elements for profiling and mapping from source to target environments

Develop supporting documents to capture findings and assign tasks.

Process claims data and extract information from sources like flat files, Oracle, and Mainframes.

Utilize data investigation, discovery, and mapping tools to scan individual records across various sources.

Conduct data analysis and profiling using complex SQL across systems such as Oracle and Teradata.

Create shell scripts using UNIX Korn shell for tasks like file transfers, error logging, data archiving, log file checks, and cleanup processes.

Integrate data from multiple sources into DOMO, using connectors to pull from databases, APIs, and cloud services.

Report on helpdesk metrics, trends, and data mining using Access.

Execute data management projects and handle ad-hoc requests with tools such as Perl, Toad, MS Access, Excel, and SQL.

Develop SQL scripts to test mappings and build a Traceability Matrix to map business requirements to test scripts, ensuring any changes lead to test case updates.

Developed complex SQL data scripts to support ETL processes and ensure accurate data transfer between source and target environments.

Troubleshooted and resolved data anomalies, ensuring high-quality data for decision-making processes.

Conduct extensive data validation by writing complex SQL queries, performing back-end testing, and addressing data quality issues.

Stay current with Azure Data Factory features and best practices, utilizing it for designing, developing, and maintaining data pipelines with integrated data validation and quality checks.

Collaborate with end users to understand core data concepts and business information needs.

Define business requirements for the IT team, creating business requirements and functional specification documents, along with mapping documents to assist developers.

Design, develop, and maintain data pipelines using Azure Data Factory, incorporating data validation and quality checks, and troubleshooting Power BI visualization issues.

Build comprehensive reports and dashboards using Power BI and Tableau, translating data into actionable insights.

Document and track defects to ensure reproducibility for the development team.

Design and develop database models for operational data stores, data warehouses, and federated databases, supporting client enterprise information management strategies.

Coordinate with offshore teams, working flexible hours as needed.

Utilize Power BI to design, build, and deploy data models and visualizations, managing Looker Explores, Views, and Dashboards for meaningful insights.

Employ advanced Excel functions (VLOOKUP, INDEX MATCH, etc.) to extract and match data across multiple datasets.

Utilize cloud-based solutions for data analytics, including AWS Glue and Azure Synapse, to optimize data processing and reporting.

Implement machine learning models using scikit-learn to enhance data-driven insights and predictive analytics capabilities.

Environment: MS SQL Server 2008 Client & Server, Oracle, Teradata, Azure Data Factory (ADF), AWS Glue, Azure Synapse, DOMO, Power BI, Tableau, Looker, MS Office (Excel, Access, PowerPoint), Legacy Mainframes, UNIX (Korn Shell), Python (Pandas, NumPy, scikit-learn), VB Scripting, VBA Macros, Hadoop (HDFS, Hive), Rational ClearQuest, ClearCase.

Client: HealthMarkets, Texas, USA Nov 2022 - Oct 2023

Role: Sr Data Analyst

Description: Healthmarkets is a leading health insurance marketplace that connects consumers with a variety of health insurance plans from top carriers. They offer a personalized online experience to help individuals and families find affordable and comprehensive coverage that meets their specific needs. Healthmarkets provides expert guidance and support throughout the enrollment process, ensuring a smooth and hassle-free experience.

Responsibilities:

Collaborated with business partners and team members to gather and analyze requirements, translating these into solutions for database designs supporting transactional systems, data integration reports, spreadsheets, and dashboards.

Involved in planning, defining, and designing databases using Erwin based on business requirements, providing comprehensive documentation.

Designed the WellPoint Facets domains, including Member, Provider, Claim, Product, and Billing Group, creating conceptual and logical models for categorizing and mapping automated business processes, user reports, and application processes to the appropriate domain entities using Erwin.

Derived logical data models from physical data models through manual reverse engineering processes.

Loaded data into Hive Tables from Hadoop Distributed File System (HDFS) to provide SQL access to Hadoop data.

Applied advanced information management and new data processing techniques to extract value from data stored in Hadoop, processing large datasets in parallel across a Hadoop cluster and utilizing the Hadoop MapReduce framework.

Worked with project management, business teams, and departments to assess and refine requirements for design and development.

Collaborated with business users and technical teams to translate project requirements into database modifications and solutions.

Protected databases by developing access control systems and specifying user levels of access to ensure data security.

Maintained user reference by writing and revising database descriptions and technical documentation.

Researched and developed hosting solutions using Tableau and other third-party hosting and software as a service solutions.

Used SQL on AWS databases like Redshift and Relational Data Services, working with various RDBMS such as Oracle 11g and SQL Server.

Worked with PivotTables on datasets up to 140 million records across multi-table structures in SQL (MS SQL Server, SAS Proc SQL, etc.).

Published reports to AWS-based Power BI services (Pro) and scheduled subscriptions with various sharing options (workspace, content pack, and apps). Designed and implemented dashboards and reports in DOMO to provide actionable insights.

Utilized Microsoft Power Query to import, clean, and transform data from various sources (Excel, CSV, databases, etc.).

Leveraged Power BI features such as DAX (Data Analysis Expressions), Power Query, and custom visuals to enhance data presentations.

Used Data Definition Language (DDL) queries to create, alter, and manage database schemas, tables, indexes, and other database objects. Utilized Data Manipulation Language (DML) queries to insert, update, delete, and select data from databases. Created Tabular Data Models and implemented Tableau for proof of concept in SharePoint environment.

Partnered directly with Data Architects, ETL developers, other technical data warehouse team members, and database administrators to design and develop high-performing databases and maintain consistent data element definitions.

Involved in data profiling for multiple sources and addressed complex business questions by providing data to stakeholders.

Created logical and physical data models, reviewing these models with the business team and data architecture team.

Transformed Logical Data Models to Physical Data Models, ensuring primary key and foreign key relationships in the Physical Data Model (PDM) and consistency of definitions of data attributes and primary index considerations.

Created SQL scripts to identify data quality issues, key data anomalies, and data validation issues.

Responsible for full data loads from production to AWS Redshift staging environment, including creating Hive tables, loading data, and writing Hive queries.

Designed various types of STAR schemas for detailed data marts and planned data marts in the OLAP environment. Enhanced data pipeline orchestration using Apache Airflow to automate data workflows and improve efficiency.

Provided architectural patterns, tooling choices, and standards for master data and hierarchy lifecycle management.

Environment: Power Pivot, SQL, MS Excel, Facets, Tableau, CSV files, Hadoop, AWS, Redshift, Python, XML files, Linux, Teradata SQL Assistant, Oracle 12c, Teradata, AWS Glue, Azure Synapse, Apache Airflow.

Client: Central Bank of India Mumbai, India May 2021 - July 2022

Role: Data Analyst

Description: Central Bank of India is a prominent public sector bank in India, offering a diverse range of financial services. From personal banking solutions like savings accounts and loans to corporate banking services like trade finance and treasury management, they cater to a wide spectrum of customers. With a strong network of branches across the country, Central Bank of India has been a reliable financial partner for individuals and businesses alike.

Responsiblities:

Led a migration project involving gap analysis between legacy systems and new platforms.

Participated in various projects focused on data modelling, data analysis, design, and development for OLTP and data warehousing environments.

Created data dictionaries, data mapping for ETL, and application support documents including DFDs, ERDs, mapping documents, metadata, DDL, and DML. Served as the primary modeller in JAD sessions to expand existing databases and develop new ones.

Developed conceptual, logical, and physical data models using Erwin based on requirements.

Worked on AWS Data Lake, migrating data to Redshift using custom SQLs, and implementing business logic via UNIX and Python scripts for analytics solutions.

Gathered requirements and designed databases using star schema, snowflake schema, and dimensional data warehouse models in Erwin.

Collaborated with cross-functional teams to review Joint Requirement Documents (QRD) and analyze high-level requirements.

Designed and developed T-SQL stored procedures for data extraction, transformation, and insertion.

Utilized Teradata utilities like Fast Export and MLOAD for various tasks, along with PL/SQL queries for data analysis and validation.

Developed dynamic and interactive reports and dashboards using Power Query and Excel, incorporating VBA for automation.

Created cross-tab, parameterized, drill-through, and sub-reports using SSRS, and developed SQL scripts for loading data from staging areas to confidential tables.

Built highly available, scalable, and self-healing systems on the AWS platform.

Defined ETL transformation rules to assist SQL developers.

Regularly collaborated with business and configuration teams to gather requirements, address design issues, and propose data-driven solutions.

Created dashboards and reports to present findings using Jupyter Notebooks, Tableau, or Power BI.

Conducted component integration testing to validate correct logic implementation between systems.

Managed updates and project details for the offshore team.

Environment: Erwin, T-SQL, OLTP, AWS, PL/SQL, OLAP, Teradata, SQL, ETL, SAS, SSRS, AWS.

Client: Revolut Mumbai, India Mar 2019 - April 2021

Role: Programmer Analyst

Description: Revolut is a fintech company that offers a mobile banking platform. It provides a variety of financial services, including multi-currency accounts, international money transfers, cryptocurrency trading, and budgeting tools. Revolut aims to simplify and modernize traditional banking by offering a convenient and affordable platform for its customers.

Responsiblities:

Created summary and tabular reports tailored to client business needs, providing data analysis and developing various business reports. Designed and developed SQL scripts to transfer data from staging tables to target tables. Optimized SQL queries for better performance, reducing spool space and CPU usage.

Utilized APIs to gather data from multiple sources, enhancing the efficiency and accuracy of data analysis.

Designed workflows for job execution and scheduled job processes, ensuring streamlined operations and timely reporting.

Performed data validation and ensured data integrity before delivering results to operations and financial analysts.

Involved in data cleaning and analysis using pivot tables, advanced formulas (including VLOOKUP, INDEX MATCH), data validation, conditional formatting, and graphical/chart manipulation.

Developed and maintained interactive dashboards using Tableau, Looker, and other data visualization tools. Analyzed large datasets to identify trends, patterns, and insights, focusing on performance tuning of slow-running SQL queries.

Developed PL/SQL scripts for automating pre- and post-session processes during data loads, ensuring data integrity and consistency.

Worked extensively with Azure Data Factory (ADF), leveraging it as a SaaS solution to integrate and orchestrate Azure data services. Integrated data from multiple databases and systems into Power BI for comprehensive analysis.

Analyzed reporting requirements and developed reports using Teradata SQL queries, MS Excel, MS Access, PowerPoint, and UNIX, ensuring alignment with business objectives.

Monitored and optimized the performance of Looker queries and dashboards, enhancing the overall user experience and data retrieval efficiency.

Environment: SAS, SQL (DDL & DML), Teradata SQL, PL/SQL, MS Excel (including advanced functions like VLOOKUP and INDEX MATCH), MS Access, PowerPoint, Power BI, Tableau, Looker, VB Scripting, VBA Macros, Python (Pandas, NumPy), Azure Data Factory (ADF), AWS Glue, Azure Synapse, Hadoop (HDFS), Hive.

EDUCATION:

Masters in Econometrics and Quantitative Economics, University of North Texas, Denton, TX.

Cumulative GPA: 3.67/4.0

Bachelor's in Finance, Minor in Hospitality, University of Delhi, New Delhi, India.

CERTIFICATIONS:

Coursera: Python for Data Science, AI & Development, AWS Certified Big Data – Specialty AWS Certified Big Data By Amazon, Microsoft Certified: Data Analyst Associate by Microsoft.

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