Kolisetty Sasiram — Associate Consultant

I’m 𝐊𝐨𝐥𝐢𝐬𝐞𝐭𝐭𝐲 𝐒𝐚𝐬𝐢𝐫𝐚𝐦, a passionate Data Engineer with a proven track record in leveraging Big Data technologies to drive business outcomes. With over 4 years of experience, I specialize in transforming raw data into valuable insights and building robust data platforms that enhance operational efficiency and decision-making. My technical skillset includes: 𝐀𝐳𝐮𝐫𝐞 𝐃𝐚𝐭𝐚 𝐅𝐚𝐜𝐭𝐨𝐫𝐲, 𝐃𝐚𝐭𝐚𝐛𝐫𝐢𝐜𝐤𝐬, 𝐝𝐛𝐭, 𝐇𝐚𝐝𝐨𝐨𝐩, 𝐀𝐩𝐚𝐜𝐡𝐞 𝐒𝐩𝐚𝐫𝐤, 𝐒𝐜𝐚𝐥𝐚, 𝐏𝐲𝐒𝐩𝐚𝐫𝐤, 𝐇𝐢𝐯𝐞, 𝐒𝐐𝐋, 𝐚𝐧𝐝 𝐍𝐨𝐒𝐐𝐋. I am also dedicated to continuously learning and staying ahead of evolving data engineering trends. In my current role as a 𝐋𝐞𝐚𝐝 𝐂𝐨𝐧𝐬𝐮𝐥𝐭𝐚𝐧𝐭 at Genpact, I architect and implement scalable, secure, and high-performance data engineering solutions for large enterprise environments. • Developed a Model-Controller Framework that streamlines complex ETL workflows. • Designed a dynamic DET framework for granular permissions management, ensuring compliance and governance across enterprise data landscapes. • Architected and optimized Databricks workflows aligned with Medallion architecture principles, achieving: 70% increase in authorized access to sensitive data and 30% boost in data processing speeds. • Engineered Azure Data Factory (ADF) pipelines, improving data throughput by 40%, resulting in $100K annual cost savings. • Tuned PySpark jobs, leading to a 40% improvement in processing efficiency. • Developed PySpark-based data cleaning pipelines, enhancing data accuracy by 15%. Beyond the technical aspects, I am passionate about building secure, reliable, and high-performance data platforms that enable organizations to unlock the full potential of their data. I thrive in challenging environments where innovation, performance tuning, and governance are top priorities. My goal is to continue evolving as a data engineering leader, driving cutting-edge data solutions that deliver measurable business impact and enable data-driven transformation across industries. If you're looking to collaborate on high-impact data engineering initiatives or need someone to help transform your organization's data into actionable insights, feel free to connect — I’m always open to meaningful conversations and new opportunities !

Stackforce AI infers this person is a Data Engineering expert in SaaS environments, specializing in Big Data technologies.

Location: Andhra Pradesh, India

Experience: 4 yrs 7 mos

Skills

Data Engineering
Big Data

Career Highlights

Led migration of 100+ workflows to Databricks.
Achieved 70% increase in data access security.
Engineered data pipelines saving $100K annually.

Work Experience

Genpact

Lead Consultant (1 yr 7 mos)

Celebal Technologies

Big Data Consultant (1 yr 10 mos)

Tata Consultancy Services

System Engineer (1 yr 2 mos)

Education

Bachelor of Technology - BTech at KL University

Intermediate at Sri Chaitanya junior kalasala

SSC at S S S Mokshith High School

Kolisetty Sasiram

Associate Consultant

Andhra Pradesh, India4 yrs 7 mos experience

Key Highlights

Led migration of 100+ workflows to Databricks.
Achieved 70% increase in data access security.
Engineered data pipelines saving $100K annually.

Stackforce AI infers this person is a Data Engineering expert in SaaS environments, specializing in Big Data technologies.

Contact

Skills

Core Skills

Data EngineeringBig Data

Other Skills

Analytical SkillsApache SparkArduinoArduino IDEAzure Data FactoryAzure Data LakeAzure DatabricksAzure Key VaultC (Programming Language)Cascading Style Sheets (CSS)Data GovernanceData IngestionData ManagementData ModelingData Pipeline

About

Experience

Genpact

Lead Consultant

Aug 2024 – Present · 1 yr 7 mos · Hyderabad, Telangana, India · On-site

Led the migration of 𝟭𝟬𝟬+ 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗰𝗮 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 to Databricks notebooks and workflows, improving scalability and long-term maintainability.
Designed and implemented 𝗮 𝗺𝗲𝘁𝗮𝗱𝗮𝘁𝗮-𝗱𝗿𝗶𝘃𝗲𝗻 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸, streamlining pipeline deployment and reducing manual intervention.
Optimized Informatica logic into efficient Spark SQL and PySpark implementations, achieving ~𝟯𝘅 faster execution times and improving pipeline reliability.
Implemented scalable processing workflows to refine and enrich data sourced from upstream ingestion frameworks for analytical and reporting use cases.
Improved ETL performance, driving ~𝟭𝟱% 𝘀𝗮𝘃𝗶𝗻𝗴𝘀 on Databricks compute costs through advanced query optimization and better resource allocation.
Spearheaded 𝗱𝗮𝘁𝗮 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 and 𝗿𝗲𝗰𝗼𝗻𝗰𝗶𝗹𝗶𝗮𝘁𝗶𝗼𝗻, ensuring high data accuracy and significantly reducing post-migration data discrepancies.
Scaled pipelines to process 𝘁𝗲𝗿𝗮𝗯𝘆𝘁𝗲𝘀 of data daily, enhancing reliability and reducing data latency.
Collaborated cross-functionally to streamline data ingestion, processing, and reporting, improving SLA adherence and operational efficiency.
Provided technical leadership in the conversion of complex Informatica mappings and optimization of existing logic, fostering a culture of performance and engineering excellence.

DatabricksAzure Data FactoryETLData ValidationData ProcessingData Engineering+1

Celebal technologies

Big Data Consultant

Oct 2022 – Aug 2024 · 1 yr 10 mos · Hyderabad, Telangana, India · Hybrid

Developed 𝐃𝐄𝐓 (𝐃𝐚𝐭𝐚 𝐄𝐧𝐭𝐢𝐭𝐥𝐞𝐦𝐞𝐧𝐭) 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤 facilitating schema and table-level permissions management, automating time-bound access permissions for Unity Catalog schemas and tables/views.
Architected and developed Databricks workflows adhering to 𝐌𝐞𝐝𝐢𝐥𝐥𝐢𝐚𝐧 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 principles, implementing seamless data ingestion and processing workflows.
Engineered processes within the customer-serving layer for seamless data delivery, incorporating functionalities such as Data Download, Data Preview, and Data Visualization. These enhancements led to a significant 𝟕𝟎% 𝐢𝐧𝐜𝐫𝐞𝐚𝐬𝐞 in authorized access to sensitive data through user entitlement-based access controls.
Spearheaded the migration of Talend workflows to Azure Cloud, optimizing code logics within Databricks, resulting in a 30% improvement in processing speed and a 𝟐𝟎% 𝐫𝐞𝐝𝐮𝐜𝐭𝐢𝐨𝐧 in operational costs.
Designed and implemented ADF pipelines for efficient data ingestion from diverse sources, achieving a 40% increase in data throughput and saving approximately $𝟏𝟎𝟎,𝟎𝟎𝟎 annually in infrastructure costs through optimized flow orchestration with Data Factory pipelines.
Proficient in tuning and optimizing Pyspark jobs for enhanced efficiency, aligning tools with business use cases for optimal performance, and leading performance tuning initiatives, resulting in a 𝟒𝟎% 𝐢𝐦𝐩𝐫𝐨𝐯𝐞𝐦𝐞𝐧𝐭 in data processing speed, as well as optimizing data pipelines, reducing 𝐜𝐨𝐬𝐭𝐬 𝐛𝐲 𝟑𝟎% while ensuring data integrity and accuracy.
Engineered Pyspark data cleaning pipelines, 𝐛𝐨𝐨𝐬𝐭𝐢𝐧𝐠 𝐝𝐚𝐭𝐚 𝐚𝐜𝐜𝐮𝐫𝐚𝐜𝐲 𝐛𝐲 𝟏𝟓% through addressing missing values, eliminating duplicates, and standardizing formats. Also, established a regulatory data quality framework for compliance.

DatabricksAzure Data FactoryData IngestionData ProcessingData QualityBig Data+1

Tata consultancy services

System Engineer

Aug 2021 – Oct 2022 · 1 yr 2 mos · Hyderabad

Experienced of importing and exporting data using 𝐒𝐪𝐨𝐨𝐩 from Relational Database Systems to HDFS and vice versa. Compiled, cleaned and manipulated data for proper handling.
Created multiple Hive tables, implemented partitioning, bucketing and other optimization techniques in Hive for efficient data access using 𝐇𝐢𝐯𝐞𝐐𝐋 language.
Implemented 𝐇𝐢𝐯𝐞 𝐨𝐩𝐭𝐢𝐦𝐢𝐳𝐞𝐝 𝐣𝐨𝐢𝐧𝐬 to gather data from different sources and run ad-hoc queries on top of them.
Increased the efficiency of the data processing by approximately 𝟑𝟎% using 𝐇𝐢𝐯𝐞 𝐨𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐭𝐞𝐜𝐡𝐧𝐢𝐪𝐮𝐞𝐬, which helped in saving costs for the project.
Implemented Spark jobs using 𝐏𝐲𝐬𝐩𝐚𝐫𝐤 and utilized Spark Structured APIs for faster processing of data.
Explored Spark jobs to improve the performance and optimization of the existing pipelines to deal with the growing data requirements. This resulted in reducing resources by 40% and fastening the process by 𝟑𝐱.
Conducted performance tuning on SQL queries, optimized data retrieval by 𝟐𝟎%.

HiveSparkSQLData ProcessingBig Data