Lead Data Engineer | New Jersey , Virginia – USA

DigitalXNode; New Jersey; On-site; USD 150,000 - 200,000; Full time

Job summary

DigitalXNode in the United States seeks a Lead Data Engineer to contribute to AI-powered risk management solutions and cloud-native data platforms. You will collaborate with engineers in an Agile environment to design, build, test, and deploy scalable data pipelines and analytics capabilities.

Lead and mentor teams while delivering secure, high-performance cloud solutions for enterprise clients, leveraging Snowflake, Redshift, Databricks, Spark, and modern cloud services across AWS, Azure, and

Qualifications

• Bachelor's or Master's Degree in a relevant discipline.
• Strong expertise in Data Engineering using Databricks, Apache Spark, Hadoop, Kafka, Hive, EMR, MapReduce, and cloud data warehouse platforms including Snowflake and Amazon Redshift.
• Proficiency in Python, Java, Scala, and SQL, with hands-on experience in full-stack development, distributed systems, microservices, and AI/ML-powered software solutions.
• Extensive experience with AWS, Microsoft Azure, and Google Cloud Platform (GCP), along with RDBMS, NoSQL databases (MongoDB, Cassandra, MySQL), UNIX/Linux, Shell Scripting, and real-time data streaming.

Responsibilities

• Collaborate with cross-functional Agile teams to design, build, test, deploy, and maintain scalable technical solutions.
• Lead and mentor software engineers working on machine learning platforms, distributed systems, cloud-native applications, and full-stack technologies.
• Design robust data engineering solutions using Python, Java, Scala.
• Develop and maintain cloud-based data warehouse solutions using Snowflake and Amazon Redshift.
• Build scalable applications utilizing both relational and NoSQL databases.
• Work with distributed computing frameworks and big data platforms to process large-scale datasets.
• Partner with Digital Product Managers and business stakeholders to deliver secure, reliable, and high-performance cloud solutions.
• Perform unit testing, peer code reviews, and performance optimization to ensure high-quality software delivery.
• Stay current with emerging technologies, cloud innovations, AI-powered engineering tools, and modern software development practices.
• Participate in internal and external technology communities while mentoring engineering teams and promoting technical excellence.

Skills

Data Engineering

Databricks

Apache Spark

Hadoop

Kafka

Hive

EMR

Snowflake

Redshift

Python

Java

Scala

SQL

AWS

Azure

GCP

NoSQL

Unix/Linux

Education

Bachelor's or Master's degree

Tools

Snowflake

Redshift

Databricks

AWS

Azure

GCP

MongoDB

Job description

Company Overview

A leading global enterprise technology organization specializing in AI-powered risk management, cloud engineering, and data-driven digital transformation solutions. With a strong focus on innovation, the company designs and delivers scalable cloud-native platforms, advanced analytics, and intelligent applications using Artificial Intelligence (AI), Machine Learning (ML), Big Data, and modern cloud technologies. Serving enterprise clients across multiple industries, the organization enables secure, high-performance, and future-ready technology solutions through expertise in AWS, Microsoft Azure, Google Cloud Platform (GCP), Databricks, Apache Spark, Snowflake, and distributed computing frameworks. The company fosters a collaborative Agile culture that encourages innovation, technical excellence, continuous learning, and leadership development while solving complex business challenges at scale.

Job Summary

Is this position for those who possess passionate vision of designing next-generation data platforms and building scalable cloud-native applications? If you enjoy solving complex enterprise challenges using modern data engineering technologies, artificial intelligence, and cloud computing, then you must apply for the opportunity.

Under an exciting opportunity an experienced Lead Data Engineer to contribute to the development of advanced risk management solutions powered by AI and machine learning. Opportunity offers you to work alongside highly skilled engineering professionals in a collaborative Agile environment while delivering innovative technology solutions that support enterprise-wide business transformation.

The in-house engineering team focuses on developing disruptive, intelligent, data-driven platforms that proactively identify and mitigate risks before it impact customers, business operations, or communities. By combining modern cloud technologies, distributed computing, and AI-powered solutions, the team delivers scalable products that drive business value and operational excellence.

Roles & Responsibilities

• Collaborate with cross-functional Agile teams to design, build, test, deploy, and maintain scalable technical solutions.


• Lead and mentor software engineers working on machine learning platforms, distributed systems, cloud-native applications, and full-stack technologies.


• Design robust data engineering solutions using modern programming languages including Python, Java, and Scala.


• Develop and maintain cloud-based data warehouse solutions using technologies such as Snowflake and Amazon Redshift.


• Build scalable applications utilizing both relational and NoSQL databases.


• Work with distributed computing frameworks and big data platforms to process large-scale datasets.


• Partner with Digital Product Managers and business stakeholders to deliver secure, reliable, and high-performance cloud solutions.


• Perform unit testing, peer code reviews, and performance optimization to ensure high-quality software delivery.


• Stay current with emerging technologies, cloud innovations, AI-powered engineering tools, and modern software development practices.


• Participate in internal and external technology communities while mentoring engineering teams and promoting technical excellence.

Required Skills

• Strong expertise in Data Engineering using Databricks, Apache Spark, Hadoop, Kafka, Hive, EMR, MapReduce, and cloud data warehouse platforms including Snowflake and Amazon Redshift.


• Proficiency in Python, Java, Scala, and SQL, with hands-on experience in full-stack application development, distributed systems, microservices, and AI/ML-powered software solutions.


• Extensive experience with AWS, Microsoft Azure, and Google Cloud Platform (GCP), along with RDBMS, NoSQL databases (MongoDB, Cassandra, MySQL), UNIX/Linux, Shell Scripting, and real-time data streaming.


• Proven leadership and Agile experience with the ability to mentor engineering teams, perform code reviews, optimize application performance, and deliver secure, scalable enterprise cloud solutions for large-scale data platforms.

Programmatic Skills

• Python, Java, Scala, SQL, Full Stack Development.

AI Experience

• AI-assisted coding tools, Machine Learning, AI-powered software development.

Managerial Experience

• Lead and mentor engineering teams; collaborate across Agile teams.

Operational Experience

• Enterprise data engineering, cloud deployment, code quality, performance optimization.

Client-Centric Experience

• Deliver secure, scalable cloud solutions supporting enterprise risk management.

Education & Certifications

• Bachelor's or Master's Degree in a relevant discipline.