Senior Data Engineer – Azure Data Lake | ETL | Data Modeling

About Company

Papigen

is a fast-growing global technology services company, delivering innovative digital solutions through deep industry experience and cutting-edge expertise. We specialize in technology transformation, enterprise modernization, and dynamic areas like Cloud, Big Data, Java, React, DevOps, and more. Our client-centric approach combines consulting, engineering, and data science to help businesses evolve and scale efficiently.

Overview

We are seeking a

senior-level Data Engineer

to lead the data and dashboard setup for a

centralized sovereign and country risk DataMart

. This role will involve designing and implementing

modern cloud-based data solutions

, working with large datasets, and collaborating across global teams to deliver high-impact analytical and reporting capabilities.

Scope Of Work

• Lead data analysis, data repository design, and data architecture for a centralized data platform.
• Collaborate with business teams to gather requirements, document data flows, and identify value-driven data solutions.
• Design ETL workflows and ensure scalable, high-performance data solutions.
• Build and optimize data repositories for analytics and reporting using Azure Data Lake and related Azure services.
• Work with Large Language Models (LLMs), modern AI capabilities, and data visualization/reporting tools to enhance insights.
• Develop and maintain metadata management and data lineage.
• Bridge technical and business teams, ensuring delivery of high-quality, maintainable solutions.
• Stay updated on data engineering best practices, cloud technologies, and emerging AI trends.
  

Required Skills & Experience

• 6–7+ years of experience in data engineering with strong data modeling and ETL design expertise.
• Proven experience designing and implementing data repositories and ETL workflows.
• Strong hands-on expertise with SQL, Oracle, and Azure Data Lake (Azure Data Stack preferred).
• Proficiency in Python and ETL tools.
• Familiarity with big data technologies like Spark and Kafka.
• Experience in data discovery and data mapping.
• Background in Capital Markets, Credit Risk Management, or Financial Risk Management is highly preferred.
• Strong collaboration skills with the ability to work in multi-location, multi-vendor teams.
  

Skills: data engineer,azure,etl,azure data lake,data modeling,spark,kafka,python,sql,azure synapse,azure data factory