Srilakshmi Ravipati

Data Engineer @ KPMG US

About

I’m Srilakshmi, a Data Engineer with 3+ years of experience designing, building, and deploying scalable real-time and batch data platforms. My expertise spans ETL/ELT development, data lakehouse architectures, and data governance frameworks that ensure high data quality, low latency, and regulatory compliance. I have hands-on experience with Apache Spark (Structured Streaming, PySpark), Apache Flink, Apache Kafka, dbt, Apache Airflow, Databricks, Delta Lake, Snowflake, AWS (S3, Redshift), along with strong proficiency in Python (Pandas, PySpark, SQLAlchemy), SQL, and dimensional data modeling (Star, Snowflake). I also have experience with Apache Atlas, Collibra, Great Expectations, and Monte Carlo for data governance and quality monitoring. I’ve successfully delivered solutions for regulatory reporting, fraud detection, and retail analytics, helping organizations achieve actionable insights and meet compliance standards. I thrive in Agile environments, collaborating with cross-functional teams to deliver advanced data engineering and analytics solutions that support business objectives and accelerate data-driven decision-making. Let's connect if you're working in cloud data engineering, analytics modernization, or real-time data platforms!

Country

United States

City

Overland Park

Industry

Information Technology & Services

Skill

Python (Pandas, PySpark, SQLAlchemy), AWS (S3, Redshift), Apache Spark (Structured Streaming, PySpark), ETL/ETL Pipelines, Data Lakehouse Architecture, Databricks, Data Build Tool (DBT), Delta Lake, Apache Atlas, SQLAlchemy, SQL, Collibra Platform, Fraud Detection, AML Monitoring, XBLR Reporting, Great Expectations, JSON parsing, Basel IV, Monte Carlo, Jira

Experience

Data Engineer

KPMG US

2024-8 - Present · 2 yrs 2 mos

Missouri, United States

Key accomplishments include: *Real-Time Data Pipelines: Designed and deployed Kafka, Flink, and Spark Structured Streaming pipelines to process daily banking transactions with <200ms latency, enabling proactive fraud and AML monitoring. *Data Lakehouse Architecture: Implemented a scalable Databricks + Delta Lake + Snowflake ecosystem to unify regulatory reporting, fraud analytics, and risk aggregation. *ETL Frameworks: Built robust Python (pandas, PySpark, SQLAlchemy) frameworks to migrate legacy mainframe systems into modern cloud-native platforms. *Regulatory Reporting: Developed dbt models for Basel IV & XBRL transformations, automating reporting with 99.5%+ accuracy and reducing manual effort by 70%. *Data Governance & Quality: Established governance using Apache Atlas & Collibra, achieving 100% dataset coverage for audit readiness. Implemented Monte Carlo & Great Expectations frameworks to maintain 99%+ SLA compliance.

Data Engineer

Accenture

2021-5 - 2023-6 · 2 yrs 2 mos

Hyderabad, Telangana, India

Key accomplishments include: *Designing Star and Snowflake schemas for efficient retail transaction analytics. *Building a data lake on AWS S3 with lifecycle policies for cost and compliance. *Developing ETL/ELT pipelines in PySpark to process millions of daily customer records. *Configuring Kafka streams for real-time order, inventory, and customer interaction data. *Creating scalable data warehouses on Amazon Redshift for sales and behavior analytics. *Orchestrating workflows with Apache Airflow, ensuring smooth omnichannel operations. *Collaborating with cross-functional teams to enhance personalization algorithms, improving customer retention by 25%.