Arjun U K

Data Scientist

Bengaluru, Karnataka, India3 yrs 11 mos experience

Highly StableAI Enabled

Key Highlights

Expert in building scalable ETL pipelines.
Reduced payment processing time by 60%.
Strong background in banking and financial analytics.

Stackforce AI infers this person is a Fintech Data Engineer specializing in automation and data analytics.

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Skills

Core Skills

Data EngineeringEtl DevelopmentData AnalysisMachine Learning

Other Skills

PySparkSQLPythonHadoopHiveAWSETL PipelinesBig Data ProcessingData ValidationData ReconciliationPayments DomainRisk AnalyticsPerformance OptimizationAutomationData Warehousing

About

Data Engineer & Data Analyst with 4+ years of experience in Banking & Financial Services, specializing in remediation analytics, large-scale transaction data processing, and business reporting. Experienced in building and optimizing ETL pipelines using PySpark, Python, AWS, and Advanced SQL to process high-volume financial datasets. Strong exposure to banking domain processes including transaction validation, reconciliation, compliance, and risk mitigation. Skilled in transforming complex data into actionable insights using Excel, Power BI, and Qlik Sense to support business decision-making. Core Technical Skills: • PySpark & Spark SQL • Advanced SQL (CTE, Window Functions, Performance Tuning) • ETL Development & Data Pipelines • Python for Data Processing & Automation • Hadoop & Hive • Excel (Advanced), Power BI, Qlik Sense • Banking Domain – Transaction Data, Remediation & Financial Risk • Cloud Exposure: GCP / AWS Passionate about building scalable data solutions, improving data accuracy, and delivering business insights within the banking ecosystem.

Experience

3 yrs 11 mos

Total Experience

3 yrs 11 mos

Average Tenure

3 yrs 11 mos

Current Experience

Anz

3 roles

Senior Data Analyst

Promoted

Sep 2024 – Present · 1 yr 9 mos · Bengaluru

Working in NFR (Non-Financial Risk) – Delivery Excellence & Payments team, driving end-to-end automation of payment and remediation processes using Big Data platforms (Cloudera Hadoop). Act as an SME for customer payments, leading payments data analysts and handling regulatory-sensitive projects to ensure accuracy and compliance.
Design and develop scalable ETL pipelines using PySpark, SQL, AWS and Python to process large-scale transactional datasets, perform end-to-end customer analysis, impact assessment, and remediation.
Built automation solutions reducing manual effort by 60% and improving turnaround time from 50 to 20 days, while optimizing data workflows and performance.
Collaborate with risk, operations, and technology teams to deliver data-driven insights, with hands-on exposure to GCP, AWS for cloud-based data processing.
Core Skills:
PySpark, SQL, Python, Hadoop, Hive, AWS, Data Engineering, ETL Pipelines, Big Data Processing, Data Analysis, Data Validation, Data Reconciliation, Payments Domain, Risk Analytics, Performance Optimization, Automation, Data Warehousing, Cloud, Bitbucket, GitHub

PySparkSQLPythonHadoopHiveAWS+15

Data Analyst

Jun 2023 – Aug 2024 · 1 yr 2 mos · Bengaluru

Designed and implemented automation solutions for payment processing using PySpark and SQL on Hadoop (Cloudera), ensuring 100% accuracy in customer payments and reducing turnaround time by 30%, significantly accelerating customer payouts.
Built automation tools and control frameworks to detect and prevent internal fraud and anomalies, while developing optimized data pipelines and collaborating with cross-functional teams to deliver scalable, efficient solutions.
Skills:
PySpark, SQL, Hadoop, Hive, Python, Data Warehousing, Data Engineering, Data Cleaning, Data Validation, Data Reconciliation, Excel, Qlik Sense, Data Visualization, Bitbucket, GitHub

PySparkSQLHadoopHivePythonData Warehousing+10

Data Analyst

May 2022 – May 2023 · 1 yr · Bengaluru

Designed and delivered an end-to-end bundled remediation solution using PySpark and SQL on Hadoop (Cloudera), consolidating multiple projects into a single pipeline and reducing turnaround time from ~50 days to 25 days.
Worked on end-to-end customer remediation, analyzing millions of records to identify discrepancies, perform impact analysis, and ensure accurate customer payments.
Performed data extraction, transformation, validation, and reconciliation while building optimized pipelines to ensure high data quality and compliance.
Did data visualization using Excel and Qlik Sense to track remediation progress and support business insights, collaborating with cross-functional teams to improve efficiency.
Skills:
PySpark, SQL, Hadoop, Hive, Python, Data Warehousing, Data Cleaning, Data Validation, Data Reconciliation, Excel, Qlik Sense, Data Visualization, Bitbucket, GitHub

PySparkSQLHadoopHivePythonData Warehousing+10

Dlithe

Data Scientist

Jun 2021 – Aug 2021 · 2 mos · Bengaluru

Performed Exploratory Data Analysis (EDA) using Python, Pandas, and Matplotlib to clean and transform datasets.
Identified data inconsistencies, missing values, and anomalies to improve data quality and reliability.
Built basic Machine Learning models for prediction and pattern identification.
Created visualizations and used SQL to extract and analyze structured data for insights.
Skills:
Python, Pandas, Matplotlib, SQL, Machine Learning, Scikit-learn, Data Cleaning, EDA, Data Visualization

PythonPandasMatplotlibSQLMachine LearningScikit-learn+4