Data Pipeline Engineer

About The Company:

Moder is an American-owned, tech-enabled outsourcing and digital transformation company specializing in the U.S. mortgage, banking, financial services, and insurance industries.

About the Role:

The Data Pipeline Engineer will design, build, and operate reliable, scalable data pipelines on Microsoft Azure. This role is responsible for ingesting, transforming, and serving data to support analytics, reporting, and AI-driven applications across the enterprise. The engineer will work closely with data consumers, application teams, and AI engineers to ensure high-quality, well-governed data flows.

Key Responsibilities:

-Design, build, and maintain end-to-end data pipelines on Azure using modern data engineering patterns (batch, streaming, ELT/ETL, event-driven ingestion).

-Implement data ingestion from diverse sources, including APIs, databases, files, event streams, and SaaS platforms.

-Develop scalable data transformation and enrichment processes to support analytics, reporting, and AI/ML workloads.

-Design and manage data storage solutions across lakehouse, warehouse, and operational data stores.

-Ensure data quality, consistency, lineage, and observability through validation, monitoring, logging, and alerting.

-Optimize pipeline performance, reliability, and cost through tuning, partitioning, scheduling, and resource management.

-Integrate data pipelines with downstream systems, including BI tools, AI/RAG workloads, and operational applications.

-Collaborate with security and governance teams to implement access controls, data protection, and compliance requirements.

-Support CI/CD practices for data pipelines, including versioning, automated testing, and environment promotion.

Skills & Requirements:

Azure Data Factory

Azure Data Lake Storage

Azure Functions

Azure Synapse Analytics

CI/CD

Event Hubs

Python

REST API

Spark

SQL

Work Experience:

5+ years of experience designing and building production data pipelines

Experience supporting AI, ML, or RAG workloads

Experience designing lakehouse or medallion-style data architectures

Degree:

Degrees like M.C.A. or B.E. or B. Tech.