Senior Data Engineer / ETL Specialist

Sai Tammineni

Sr. ETL Developer/ Data Engineer

Contact: +1-469-***-****

Email: ****************@*****.***

LinkedIn: https://www.linkedin.com/in/sai-t-186337392/

SUMMARY OF QUALIFICATIONS

Versatile Senior Data Engineer / ETL Integration Engineer with strong experience designing, developing, and supporting enterprise data ingestion, ETL/ELT, data warehouse, and cloud data platform solutions. Hands-on experience with Snowflake, Informatica PowerCenter/IICS, SQL, Python, AWS, Airflow-based orchestration, APIs, flat files, CDC-style ingestion, source-to-target mapping, data validation, reconciliation, and production pipeline support. Skilled in onboarding new data sources, building scalable batch and near real-time integration workflows, monitoring ingestion failures, optimizing SQL transformations, and supporting analytics-ready warehouse models for business, product, and reporting teams.

PROFESSIONAL SUMMARY

Senior ETL / Cloud Data Engineer experienced in building and modernizing enterprise ETL/ELT pipelines, cloud data platforms, and large-scale analytics solutions across travel, financial services, and enterprise domains.

Strong expertise in Snowflake, SQL, Python, AWS, Azure, Informatica, and SSIS with hands-on experience designing scalable data warehousing and reporting modernization solutions.

Experienced in migrating legacy ETL ecosystems and on-premise warehouse workloads into modern cloud-based analytics architectures supporting enterprise reporting and operational insights.

Designed and optimized high-volume batch and near real-time ingestion pipelines supporting multi-million-row analytics, reconciliation, and reporting workloads.

Built automated data validation, reconciliation, and audit logging frameworks improving data reliability, traceability, and operational stability across enterprise reporting systems.

Hands-on experience working with Snowflake features including Streams, Tasks, Dynamic Tables, workload optimization, RBAC, and cloud-native ELT processing strategies.

Developed Python-based ingestion and automation frameworks for API integration, transformation orchestration, operational monitoring, and reporting workflows.

Experience supporting scalable analytics and distributed processing initiatives using Databricks, PySpark, Delta Lake, and modern transformation approaches.

Collaborated with business, analytics, finance, operations, and reporting teams to translate complex data requirements into reliable and scalable engineering solutions.

Strong background in dimensional modeling, SCD Type 1/2 implementation, staging-to-mart architectures, data warehousing, and enterprise reporting optimization.

Experience supporting CI/CD-driven deployment processes, pipeline monitoring, scheduling, and modernization initiatives across enterprise cloud data platforms.

Exposure to AI-enabled analytics initiatives involving intelligent reporting workflows, metadata enrichment, and cloud-based GenAI-assisted operational analysis.

TECHNICAL SKILLS:

Category

Skills

Programming Languages

SQL, Python, PySpark, Shell Scripting

Cloud Platforms

AWS, Azure, Snowflake, Databricks, GCP, Vertex AI Exposure

ETL / ELT Tools

Informatica PowerCenter, Informatica IICS, SSIS, Airflow, CDC Pipelines

Data Engineering

ETL/ELT, Data Warehousing, Data Modeling, Dimensional Modeling, SCD Type 1/2, Medallion Architecture

Databases

Snowflake, SQL Server, Oracle, PostgreSQL, Redshift

Big Data Technologies

Databricks, PySpark, Delta Lake, DLT

Reporting & Analytics

Power BI, Tableau, SSRS

Cloud Services

AWS S3, Lambda, Glue, DMS, CloudWatch, Azure Data Factory

Automation & Monitoring

CI/CD, Pipeline Optimization, API Ingestion, Observability, Data Validation, Monitoring

Governance & Security

RBAC, Audit Logging, Data Reconciliation, Data Quality Frameworks

Version Control & Methodologies

Git, Agile, Scrum

PROJECT DETAILS

Client: Princess Cruises Apr 2025 – Present

Client Summary:

Princess Cruises is a global cruise and travel organization operating large-scale booking, voyage, revenue, and operational analytics systems across customer and enterprise platforms. The organization initiated a cloud modernization effort focused on analytics scalability, reporting and operational visibility across enterprise data ecosystems.

Location: Santa Clarita, CA

Role: Senior Data Engineer

Project Description

Oracle to Snowflake Cloud Data Platform Modernization

Worked on a cloud data platform modernization initiative focused on migrating legacy warehouse workloads into a Snowflake-based analytics architecture on AWS. The platform supported booking, voyage, customer, and revenue analytics while improving reporting performance, operational monitoring, and near real-time data availability. Designed scalable ELT pipelines, API ingestion frameworks, and automated validation processes supporting enterprise analytics and executive reporting workloads. Collaborated with analytics and business teams to improve data reliability, warehouse optimization, and reporting modernization initiatives.

Roles & Responsibilities

Designed and optimized Snowflake-based ELT pipelines supporting enterprise booking, voyage, and operational analytics workloads across multiple business domains.

Supported orchestration and scheduling workflows for Snowflake ingestion pipelines using Airflow-based job monitoring approaches.

Developed scalable ingestion frameworks using Python and REST APIs to process reservation, customer, and operational datasets from external platforms.

Implemented Snowflake Streams, Tasks, and Dynamic Tables supporting automated incremental processing and near real-time reporting workflows.

Supported migration of legacy warehouse workloads into AWS and Snowflake environments improving scalability, query performance, and operational reliability.

Built automated validation and reconciliation processes ensuring consistency across staging, warehouse, and reporting layers.

Optimized Snowflake warehouse utilization, query execution patterns, and workload distribution strategies for high-volume reporting environments.

Developed reusable SQL transformation frameworks supporting dimensional models, curated marts, and executive reporting datasets.

Collaborated with analytics and reporting teams to modernize Power BI dashboards and improve operational reporting accessibility.

Implemented monitoring and observability processes using CloudWatch and operational logging frameworks improving pipeline reliability and troubleshooting.

Worked with RBAC policies, secure data access strategies, and audit logging controls supporting enterprise governance requirements.

Participated in modernization initiatives involving AI-assisted analytics exploration and intelligent metadata-driven reporting workflows.

Supported CI/CD-driven deployment and release processes for Snowflake objects, ingestion pipelines, and reporting integrations.

Environment: Snowflake, AWS S3, Lambda, DMS, Python, SQL, Informatica IICS, Streams & Tasks, Dynamic Tables, REST APIs, Power BI, CloudWatch, Git, CI/CD, Agile.

Client: British Petroleum (BP America) Jan 2024 – Mar 2025

Client Summary: BP America operates enterprise-scale energy trading, finance, and risk analytics platforms supporting exposure management and operational reporting. The organization relied on centralized warehousing and reporting systems for credit exposure calculations, reconciliation, governance, and regulatory reporting workflows.

Location: Houston, TX

Role: Lead ETL / Data Warehousing Engineer

Project Description

Credit Exposure & Risk Analytics Data Warehouse

Worked on an enterprise Credit Exposure & Risk Analytics Data Warehouse supporting trading, finance, and operational reporting teams. The platform integrated large-scale transactional, settlement, and counterparty datasets into centralized reporting and analytics systems. Designed scalable ETL workflows, validation frameworks, and dimensional warehouse models supporting reconciliation, governance, and exposure analytics. Focused heavily on enterprise data quality, reporting modernization, and operational stability across daily batch processing environments.

Roles & Responsibilities

Designed and maintained enterprise ETL pipelines processing large-scale trading, settlement, and counterparty datasets for exposure analytics and operational reporting.

Developed Informatica PowerCenter and SSIS workflows supporting batch ingestion, transformation, reconciliation, and warehouse loading processes.

Built dimensional data models and implemented SCD Type 1/2 strategies supporting historical reporting and exposure analysis requirements.

Developed complex PL/SQL transformation logic and optimized SQL workloads improving batch execution efficiency and reporting performance.

Created automated reconciliation and audit validation frameworks ensuring consistency between source systems, staging layers, and warehouse outputs.

Supported enterprise reporting modernization initiatives by integrating curated warehouse datasets into Power BI reporting environments.

Collaborated with finance, risk, and analytics teams to analyze business rules and improve reporting accuracy across enterprise systems.

Worked on Oracle and PostgreSQL warehouse environments supporting high-volume analytical and regulatory reporting workloads.

Implemented operational monitoring, failure handling, and restart mechanisms improving ETL reliability and reducing production support issues.

Participated in data governance and lineage initiatives supporting traceability, validation, and enterprise reporting standards.

Optimized staging and transformation processes for high-volume reporting cycles and reconciliation workloads.

Supported release management, deployment activities, and production support processes across multi-environment ETL ecosystems.

Environment: Informatica PowerCenter, SSIS, SQL, PL/SQL, Oracle, PostgreSQL, Power BI, Data Warehousing, SCD Type 1/2, UNIX Shell Scripting, Git, Agile.

Client: Transunion Sep 2021 – Dec 2023

Client Summary: TransUnion is a global information and analytics organization supporting enterprise-scale consumer data, reporting, and analytics operations across financial and operational domains. The organization focused on modernizing reporting pipelines and improving scalable analytics processing across cloud-enabled data platforms

Location: Chicago, IL

Role: Sr ETL Developer

Project Description:

Worked on enterprise data modernization initiatives focused on scalable transformation processing, analytics optimization, and reporting pipeline improvements. Supported distributed processing and cloud-based transformation workloads using Databricks and PySpark while improving operational efficiency and reporting reliability. Built scalable ingestion, validation, and transformation processes supporting enterprise analytics and operational reporting. Contributed to modernization efforts involving medallion-style data processing and optimized analytics delivery pipelines

Roles & Responsibilities

Developed scalable ETL and ELT workflows supporting enterprise reporting, analytical processing, and large-volume data integration requirements.

Worked with Databricks and PySpark transformation pipelines processing high-volume structured and semi-structured datasets.

Supported Delta Lake-based processing workflows and curated transformation layers for downstream reporting and analytical consumption.

Built reusable SQL and Python-based transformation frameworks improving maintainability and operational consistency across ingestion pipelines.

Developed automated data validation and quality checks supporting reporting accuracy and operational stability across enterprise datasets.

Collaborated with reporting and analytics teams to improve data delivery processes supporting Power BI and operational reporting environments.

Participated in modernization initiatives involving medallion-style layered processing and scalable cloud-based transformation workflows.

Optimized transformation logic and query execution strategies improving pipeline performance and batch processing efficiency.

Worked with Azure-based ingestion and orchestration workflows supporting enterprise reporting and distributed analytics processing.

Assisted with operational troubleshooting, production support, root cause analysis, and batch failure resolution activities.

Contributed to CI/CD deployment activities and migration initiatives supporting cloud modernization and scalable analytics processing.

Supported operational monitoring and reporting validation processes improving data reliability and downstream reporting consistency.

Environment: Azure, Databricks, PySpark, Delta Lake, DLT, Python, SQL, Power BI, Azure Data Factory, ETL/ELT, Git, CI/CD, Agile

Client: Spectra Systems, Hyderabad, India Jun 2020 – Aug 2021

Location: Hyderabad, India

Role: SQL Server / SSIS / ETL Developer

Roles & Responsibilities

Developed SSIS packages and SQL Server-based ETL workflows supporting enterprise reporting and operational data integration requirements.

Created stored procedures, SQL transformations, and validation queries supporting reporting accuracy and warehouse processing activities.

Assisted with ETL enhancement initiatives involving staging optimization, transformation improvements, and reporting workflow automation.

Developed reconciliation and data validation logic to identify inconsistencies and improve operational reporting quality.

Supported batch processing activities, production deployments, and issue resolution across SQL Server reporting environments.

Worked with reporting teams to support SSRS and operational reporting workflows for business and analytical reporting requirements.

Optimized SQL queries, indexes, and transformation logic improving batch execution performance and reporting responsiveness.

Participated in ETL troubleshooting, root cause analysis, and production support activities across multiple reporting workflows.

Assisted with migration and enhancement initiatives supporting improved warehouse processing and reporting scalability.

Collaborated with business and technical teams to analyze reporting requirements and improve ETL processing reliability.

Supported release validation, deployment coordination, and post-production verification activities across ETL environments.

Maintained operational documentation, workflow mapping, and support processes for reporting and integration systems.

Environment: SQL Server, SSIS, T-SQL, Stored Procedures, SSRS, Power BI, ETL, Data Validation, SQL Optimization, Git, Agile.

EDUCATION

Master's in computer science from Texas A&M University.

Bachelor's in information technology from VJIT.

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