Job Description

Immediate Hiring - Walbrydge Technologies

Role Overview

Walbrydge Technologies is hiring

Data Engineers

to design and build the

core data infrastructure

that powers real-time analytics, operational intelligence, and machine learning pipelines across our enterprise ecosystem.

This role is critical to enabling

high-quality, scalable, and reliable data platforms

that support real-time dashboards, analytics, and future AI-driven capabilities.

Position Details

Role:

Data Engineer - Platform & Analytics Infrastructure

Experience:

5-8 Years

Positions:

3

Location:

Hyderabad, India(Offshore)

Employment Type:

Full-Time

Start Date:

1-2 Weeks

Interested candidates may send their resume to: info@walbrydge.com

Key Responsibilities

Data Platform & Pipeline Engineering

Design and implement

end-to-end data pipelines

supporting both

batch and real-time streaming workloads

. Build and maintain

ETL / ELT workflows

using modern data engineering tools. Architect and manage

data lakes, data warehouses, and real-time event pipelines

.

Data Ingestion & Processing

Develop scalable ingestion pipelines from

distributed microservices, APIs, and event streams

. Implement real-time data processing using

Kafka, Spark Streaming, Flink, or equivalent technologies

. Optimize pipelines for

latency, throughput, and fault tolerance

.

Data Quality, Governance & Optimization

Implement

data quality checks, validation rules, lineage tracking, and governance standards

. Design efficient

data models, partitioning strategies, and schema evolution

. Optimize storage and compute for

performance, scalability, and cost efficiency

.

Cross-Functional Collaboration

Work closely with

ML Engineers, Data Scientists, Backend Engineers, and DevOps teams

. Support analytics, reporting, and ML feature pipelines with clean, reliable datasets. Ensure

security, access control, and compliance

across all data systems.

Required Skills & Experience

Core Technical Skills

5-8 years of professional experience in

Data Engineering

. Strong proficiency in

Python and SQL

. Hands-on experience with

ETL/ELT orchestration tools

such as

Airflow, dbt

, or similar. Experience building

streaming and event-driven pipelines

using

Kafka, Kinesis, Spark Streaming, or Flink

.

Data Storage & Analytics Platforms

Strong experience with data warehouses such as:

Snowflake, Redshift, BigQuery, Azure Synapse, or Databricks

Hands-on experience with data lakes:

AWS S3, Azure Data Lake (ADLS), or Google Cloud Storage (GCS)

Platform & Architecture Knowledge

Strong understanding of

data modeling, schema design, partitioning, and indexing

. Experience with

API-based ingestion and real-time event streaming

. Familiarity with

CI/CD pipelines, containerization, and cloud-native architectures

.
Job Types: Full-time, Permanent

Benefits:

Flexible schedule Food provided Health insurance Leave encashment Paid sick time Paid time off Provident Fund Work from home
Work Location: In person