Data Engineer Senior

KONDA REDDY LEKKALA

Dallas, Texas, USA **********@*****.*** +1-818**-***** LinkedIn: https://www.linkedin.com/in/kondareddy-lekkala-461b4264/

PROFESSIONAL SUMMARY

Accomplished Senior Data Engineer with over 14 years of experience building high-performance ETL and big data solutions across Banking, Finance, Insurance, Retail, and Healthcare industries. Expert in Ab Initio, Spark, Informatica, Kafka, Snowflake, and cloud platforms (Azure, AWS). Proven ability to modernize legacy systems, design scalable data pipelines, and drive data-driven decision-making in enterprise environments.

️ TECHNICAL SKILLS

ETL & Orchestration: Ab Initio, Informatica, ADF, Azure Databricks, DBT, Control-M, Autosys, Airflow

Big Data & Cloud: Apache Spark, Hadoop, HDFS, Hive, Snowflake, AWS, Azure

Programming: Python, SQL, Unix Shell Scripting, PL/SQL

Streaming & Monitoring: Kafka, Splunk, Jenkins, Azure Monitor

Databases: Oracle, Teradata, Snowflake, DB2

Versioning & Tools: Git, EME, ServiceNow, SVN

PROFESSIONAL EXPERIENCE

**Senior Data Engineer Vass Soft Inc**

**Client: Geico Insurance (Nov 2024 – Present)**

- Migrated critical DB2 datasets to Snowflake using Ab Initio Graphs, ensuring data integrity.

- Designed and built scalable ETL pipelines aligned with cloud transformation strategies.

- Performed detailed data validation and transformation using custom Ab Initio graphs.

- Led production deployment, post-deployment validation, and reconciliation activities.

- Collaborated with cloud architects for optimizing Snowflake compute resource utilization.

- Developed monitoring dashboards using Splunk for real-time issue tracking.

- Documented ETL mappings, technical specifications, and troubleshooting guides.

**Client: Molina Healthcare, CA (Oct 2023 – Present)**

- Built complex data pipelines in Azure Data Factory, integrating diverse sources.

- Developed PySpark scripts in Azure Databricks to process and transform healthcare claims data.

- Implemented Kafka-based streaming for near real-time ingestion of provider data.

- Automated data quality checks and reporting using Databricks notebooks.

- Designed reusable modules for parameter-driven pipeline development.

- Ensured HIPAA compliance across all transformation and storage layers.

- Provided knowledge transfer and mentoring to junior data engineers.

**Client: JPMorgan Chase, TX (Nov 2021 – Sep 2023)**

- Migrated traditional ETL processes to PySpark and Hive on the Hadoop ecosystem.

- Refactored risk aggregation pipelines for high throughput and low latency.

- Managed Jenkins-based CI/CD pipelines and streamlined deployment cycles.

- Integrated Airflow for orchestration and alerting across critical jobs.

- Tuned Spark jobs for optimal memory and executor utilization.

- Worked with the data governance team to ensure lineage and audit compliance.

- Participated in architecture review and capacity planning sessions.

**Client: Discover Finance, IL (Sep 2020 – Oct 2021)**

- Modernized GL processes using Ab Initio integrated with Oracle Cloud Financials.

- Automated month-end close reports, reducing cycle time by 30%.

- Developed reusable business rules and validation graphs in Ab Initio.

- Coordinated with finance stakeholders to define data requirements.

- Implemented role-based access and audit logging for compliance.

- Streamlined legacy job monitoring via custom control frameworks.

- Enabled historical data reconciliation using automated audit scripts.

**Client: Allstate Insurance, IL (Feb 2020 – Aug 2020)**

- Migrated ETL jobs from legacy file systems to HDFS-based storage.

- Designed reusable Ab Initio graph templates for faster development.

- Reduced runtime of critical jobs by 40% using partitioning and optimization.

- Created metadata-driven automation framework for job orchestration.

- Established end-to-end data lineage using Metadata Hub.

- Conducted peer code reviews and implemented coding standards.

- Developed rollback and error recovery procedures for production support.

**ETL/Ab Initio Admin Persistent Systems**

**Client: Wells Fargo (Sep 2018 – Feb 2020) **

- Migrated ETL workflows to Hadoop-based Data Lake using Ab Initio.

- Implemented Metadata Hub for lineage, impact analysis, and data discovery.

- Designed high-performance multi-partition ETL flows.

- Tuned batch windows to meet SLA and batch deadlines.

- Created health monitoring scripts and alerts using Unix Shell and Splunk.

- Automated deployment processes using Jenkins and Git.

- Provided on-call production support and RCA for failures.

**Senior Software Engineer KC Synergy Solutions / TCS**

**Clients: Wells Fargo, SunTrust, HP, JPM Chase (2015 – 2018)**

- Re-engineered legacy ETL flows with standardized templates.

- Migrated ETL logic to Hadoop and Spark frameworks.

- Designed parameterized graphs and common library components.

- Implemented restartability and recovery within critical workflows.

- Conducted performance benchmarking and tuning.

- Developed data quality frameworks to ensure consistency.

- Led batch migration initiatives across multiple LOBs.

**Software Engineer Accenture / HCL Technologies**

**Clients: Citi Bank, NAB (2010 – 2015)**

- Built regulatory data marts for Basel and Volcker Rule compliance.

- Designed ETL mappings with audit and traceability.

- Developed reusable components for common transformations.

- Validated reporting data against regulatory guidelines.

- Automated reconciliation of risk and exposure metrics.

- Supported UAT and production rollouts for compliance releases.

- Worked closely with business analysts and risk officers.

EDUCATION

Master of Computer Applications (MCA)

Jawaharlal Nehru University, Hyderabad – 2009

Bachelor of Computer Science

Sri Venkateshwara University, Andhra Pradesh – 2004

PROJECT HIGHLIGHTS

Real-Time Risk Platform: Migrated and redesigned risk data workflows using Kafka, Spark, and Snowflake, enabling 24/7 data availability and reducing SLA breaches by 60%.

Legacy ETL Modernization: Transitioned 100+ Ab Initio workflows to PySpark, cutting operational costs and improving scalability.

Data Lake Enablement: Led multi-client Hadoop data lake integration projects, ensuring governance, performance, and real-time data delivery.

TOOLS & ENVIRONMENTS

Jenkins, Splunk, Azure Monitor, Git, EME, Jira, ServiceNow, HP ALM

References available upon request

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