Shivam Birla

/ˈʃɪv.əm ˈbɪr.lə/ • noun •

00:00:00 IST

• Bengaluru, India

a data engineer with 2 years of experience building, optimizing, and supporting enterprise ETL pipelines and data warehousing workflows using Oracle Data Integrator (ODI) and Informatica.

delivered high-impact data solutions for retail (IKEA) and banking (MUFG Bank) clients at Capgemini. a Mathematics & Computing graduate from NIT with strong SQL skills, a solid foundation in data structures and algorithms (1,000+ problems solved, LeetCode 1726, Codeforces 1301), and completed coursework in GCP, Docker, Kubernetes, and Terraform.

Experience Nov 2024 — Jan 2027

Capgemini

Senior Analyst (Data Engineer) • Bengaluru, India

Nov 2024 – Jan 2027

Client: IKEA

Data Engineering – ETL & Data Warehousing

ODI ETL Pipelines: Developed and enhanced Oracle Data Integrator (ODI) mappings, packages, and scenarios to extract, transform, and load retail transaction and store data from source systems into the central Oracle data warehouse.
Change Data Capture (CDC): Built and supported Change Data Capture (CDC) and baseload pipelines, reprocessing and reconciling loads after failures to keep downstream data consistent and complete.
Oracle SQL Optimization: Wrote and tuned Oracle SQL for data validation, data quality checks, and reconciliation, and for new store onboarding across environments.
Middleware & Error Resolution: Supported critical real-time transactional data flows in Oracle SOA Suite, resolving error queues in WebLogic and finding root causes of message and data failures.
GCP Cloud Observability: Monitored cloud-based data flows on Google Cloud Platform (Cloud Run), troubleshooting failures from logs and alerts and tracking incidents in ServiceNow and Jira.

Client: MUFG Bank

Data Engineering – ETL Development

Informatica PowerCenter: Developed and maintained Informatica PowerCenter mappings, sessions, and workflows to load banking data into target data warehouse tables.
Data Reconciliation: Validated and reconciled loaded data against source systems using SQL to ensure accuracy for downstream reporting.
Batch Pipeline SLA: Monitored scheduled batch pipelines, investigated job failures, and applied fixes or reruns to meet batch processing SLAs.

Cloud & DevOps (Coursework) Practical Labs

Completed intensive coursework and practical hands-on labs covering Google Cloud Platform (GCP, Cloud Run), Docker containerization, Kubernetes cluster management, Infrastructure as Code with Terraform, advanced Git workflows, and Linux OS administration.

Achievements & Metrics Quantified Milestones

98.6% JEE Mains Percentile Top tier in India (1.2M+ test takers)

Cracked JEE Advanced Premier engineering qualifier

1000+ Problems Solved Across competitive platforms

1726 LeetCode Peak Rating • Codeforces: 1301

Generalist by Heart, Specialist by Profession

Oracle SQL

ODI (ETL)

Informatica

Ab Initio

Google Cloud

Docker & K8s

Terraform

Python & SQL

C++

SOA & WebLogic

Oracle SQL

ODI (ETL)

Informatica

Ab Initio

Google Cloud

Docker & K8s

Terraform

Python & SQL

C++

SOA & WebLogic

Languages

Python SQL (Oracle SQL, PL/SQL, Analytical Queries) C++ Bash / Shell Scripting

Data Engineering & ETL

Oracle Data Integrator (ODI) Informatica PowerCenter Ab Initio ETL Development Data Warehousing Data Pipelines Change Data Capture (CDC) Data Quality & Validation Performance Tuning

Databases & Middleware

Oracle SQL Database Oracle SOA Suite WebLogic Server Data Reconciliation Schema Management

Cloud & DevOps (Coursework)

Google Cloud Platform (GCP) GCP Cloud Run Docker Kubernetes Terraform Git & GitHub Linux

Tools & Operations

ServiceNow Jira

Featured Data Architectures Enterprise Workflows

IKEA Retail CDC & Cloud Run Pipeline Enterprise Retail Architecture

End-to-end Change Data Capture (CDC) and baseload pipeline designed for continuous data synchronization between worldwide physical retail store systems and centralized cloud data warehouses. Implements automated health checks, Pub/Sub event queues, and Terraform-orchestrated Cloud Run container monitoring.

01. Ingestion & CDC

Oracle SQL & ODI tracking real-time transactional logs and retail store baseload.

02. Event Stream

Google Cloud Pub/Sub decoupling store events with zero message drop.

03. Cloud Run & Alerts

Automated serverless processing, monitoring dashboards, and WebLogic error queues.

Oracle Data Integrator GCP Cloud Run Change Data Capture Terraform IaC Oracle SOA

MUFG Bank Batch ETL & Reporting Warehouse Financial Data Engineering

High-reliability batch data warehousing pipeline developed for banking operations. Loads and reconciles banking records into target data warehouse tables using Informatica PowerCenter sessions, enforcing strict data accuracy and monitoring batch schedules to guarantee SLA adherence.

01. Banking Feeds

Extracting high-volume transactional feeds into structured staging layers.

02. PowerCenter Workflows

Informatica mappings and session workflows transforming & loading target DW tables.

03. SQL Reconciliation & SLAs

Automated data validation against source systems and SLA failure alerting.

Informatica PowerCenter Data Warehousing SQL Reconciliation Batch Processing SLA Monitoring

In Between These Experiences Engineering Journey

From Algorithmic Invariants to Enterprise Scale

My foundation started in Mathematics and Computing at the National Institute of Technology. Immersing myself in discrete structures, linear algebra, and competitive programming taught me to see complex data systems not as arbitrary code, but as deterministic state machines and algorithmic invariants.

Solving over 1,000 algorithmic problems across LeetCode (Rating 1726) and Codeforces (Rating 1301) forged the discipline to obsess over computational complexity, edge cases, and data integrity.

At Capgemini delivering data solutions for IKEA and MUFG Bank, that problem-solving intuition translates into mission-critical enterprise reliability: architecting Oracle ODI and Informatica PowerCenter ETL workflows, optimizing Oracle SQL queries, handling real-time WebLogic error queues, and ensuring cloud-based data flows maintain absolute consistency across global operations.

Education Oct 2020 — June 2024

NIT

National Institute of Technology

Bachelor of Technology in Mathematics and Computing

Oct 2020 – June 2024

Rigorous curriculum combining theoretical computer science with applied mathematics: Data Structures & Algorithms, Object-Oriented Programming, Database Management Systems (DBMS), Operating Systems, Computer Networks, Linear Algebra, Probability & Statistics, and Discrete Mathematics.

Get in Touch Open for Opportunities

Let's build reliable data systems together

Open to Data Engineering, ETL development, and backend data systems opportunities, collaborations, and technical discussions. Drop me a note or reach out directly.

Email Me