Event Streaming Developer

Burns & McDonnell; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Burns & McDonnell Bengaluru is seeking a senior data engineer who combines an architecture mindset with hands-on experience to own end-to-end pipelines on Google Cloud. You’ll architect data platform solutions, build production data flows from source systems (Oracle, CRM) to GCS and BigQuery, and deliver scalable data products for multiple business units.

The role emphasizes hands-on coding, reliability, IAM governance, and CIM semantic layers, plus applying Vertex AI and other GCP services to

Qualifications

• 7–10 years of work experience in IT/data engineering.
• BCA / MCA / B.TECH in Information Technology required.
• Job posting open minimum 72 hours and until filled.
• Primary location: Bengaluru, India.

Responsibilities

• Architect end-to-end data platform solutions: from source system connectivity through ingestion, storage, transformation, and data product delivery.
• Build and ship production pipelines from source systems (Oracle, CRM, engineering apps) to Google Cloud Storage and BigQuery.
• Develop multimodal unstructured data processing workflows (PDFs, Excel, PowerPoint, audio, video, drawings).
• Apply Google Cloud AI services to extract structured information and ship results to production datasets.
• Use LLMs to classify and transform unstructured text and documents into structured data products.
• Maintain CIM semantic layers aligned with business-domain meaning across practices.
• Design and manage Google Cloud Storage buckets with lifecycle policies and cost optimization.
• Configure IAM and least-privilege policies across platform resources.
• Build observability into pipelines with logging, alerts, data quality checks, and SLA monitoring.

Skills

Architecture mindset

Production engineering

Google Cloud Platform

Unstructured data processing

AI transformation

Data engineering

Python

SQL (BigQuery)

dbt

ELT/ETL design

Data modeling

Git CI/CD

Terraform IaC

Security governance

Education

BCA / MCA / B.TECH in Information Technology

Tools

BigQuery

Cloud Storage

Dataflow

Airflow

Pub/Sub

Vertex AI

Cloud Composer

Cloud IAM

Job description

Description

Google Cloud

• Architecture Mindset

• Hands-On Pipeline & Production Builder

Experience Required 7-10 years

We are building a central Data Engineering team responsible for ingesting data from enterprise source systems and engineering applications — including Oracle, CRM platforms, and internal engineering tools — loading it into our data platform and delivering foundational data products that serve Group Practices across the firm. We're looking for a senior engineer who combines an architecture mindset with deep hands‑on experience — someone who can design scalable systems and personally build and ship them into production. You will own pipelines end-to-end, from whiteboard to running code, on Google Cloud.

What You’ll Do

ARCHITECTURE & DESIGN

Architect end-to-end data platform solutions: from source system connectivity through ingestion, storage, transformation, and data product delivery — making deliberate decisions on scalability, cost, and maintainability.

Define reference architectures and reusable patterns: for pipelines, storage layout, IAM boundaries, and CIM modeling that the whole engineering team builds from.

Evaluate and select Google Cloud services: for each workload: streaming vs. batch, event-driven vs. scheduled, structured vs. unstructured.

Translate business requirements: from Portfolio Data Managers and domain data owners into clear, implementable technical designs.

HANDS-ON PIPELINE & PRODUCTION ENGINEERING

Personally build and ship production pipelines: this role codes, not just designs. You will own your work from first commit through deployment, monitoring, and ongoing reliability.

Build end-to-end ingestion pipelines: from source systems (Oracle, CRM, engineering applications) into Google Cloud Storage and BigQuery.

Build multimodal unstructured data processing workflows: handling PDFs, Excel, PowerPoint, audio recordings, video files, and engineering drawings.

Apply Google Cloud AI services: Document AI, Speech-to-Text, Video Intelligence, Vision API, Vertex AI — to extract structured information from unstructured content and ship results to production datasets.

Use LLMs: to classify, summarize, and transform unstructured text and documents into structured, queryable data products.

Build and maintain Common Information Model (CIM) semantic layers: aligning ingested data with business-domain meaning across Group Practices.

Design and manage Google Cloud Storage buckets: lifecycle policies, folder structure, access controls, and cost optimization.

Configure and enforce Google Cloud IAM: service accounts, role bindings, workload identity, and least‑privilege policies across all platform resources.

Write observability into every pipeline: logging, alerting, data quality checks, and SLA monitoring from day one.

Required Skills

ARCHITECTURE MINDSET & PRODUCTION ENGINEERING

Proven record of designing systems and then personally building them for production, not delegating implementation after the whiteboard session.

Architecture trade‑off decisions: streaming vs. batch, managed vs. custom, normalized vs. denormalized — and the ability to explain the reasoning clearly.

Reliability patterns: idempotency, dead‑letter queues, retry logic, schema evolution, and data quality gates.

Technical design documents that a team can build from, and are equally comfortable writing the code.

GOOGLE CLOUD PLATFORM

BigQuery

• Cloud Storage (GCS)

• Cloud IAM

• Dataflow / Apache Beam

• Cloud Composer / Airflow

• Pub/Sub

• Vertex AI

• Cloud Functions / Run

UNSTRUCTURED DATA & AI TRANSFORMATION

Google Document AI

• Speech-to-Text API

• Video Intelligence API

• Vision API / OCR

• PDF & Office file parsing

• Audio processing

• Engineering drawing extraction

• LLM-based data extraction

DATA ENGINEERING FUNDAMENTALS

Python

• SQL (BigQuery dialect)

• dbt

• ELT / ETL pipeline design

• Data modeling

• Git / CI-CD

• Terraform / IaC

SECURITY & GOVERNANCE

Google Cloud IAM: service accounts, custom roles, workload identity federation, least‑privilege design across projects and datasets.

GCS access controls: uniform bucket-level access, IAM conditions, VPC Service Controls, audit logging.

DATA MODELING & CIM

Common Information Model (CIM): experience building CIM semantic layers — ideally in energy, utilities, or infrastructure domains (IEC 61968 / 61970).

Source‑aligned data products: faithful to source systems, enriched with business-domain meaning ("zero layer").

Dimensional modeling: medallion architecture (bronze / silver / gold), and structuring data for downstream BI and AI consumers.

Qualifications

The candidate should have a BCA / MCA / B.TECH degree in Information Technology. The candidate should have a work experience of 7-10 years.

This job posting will remain open a minimum of 72 hours and on an ongoing basis until filled.

Job Information Technology

Primary Location India-Karnataka-Bengaluru

Schedule: Full-time

Travel: No

Job Hire Type Experienced Not Applicable #BMI N/A