Technical Lead & Data Architect

DXC Technology•Newark, NJ

1d•$126,600 - $235,100•Onsite

About The Position

The ideal candidate combines deep expertise in cloud-based data architecture with hands-on technical leadership experience in delivering modern ETL pipelines and data engineering solutions within AWS environments.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.
8+ years of experience in data engineering, ETL development, or data architecture.
3+ years of experience leading technical teams or serving in a technical lead capacity.
Strong hands-on experience with AWS cloud services and data platforms.
Deep expertise in ETL/ELT architecture and implementation.
Strong proficiency in SQL and Python.
Experience with cloud-based data lakes, data warehouses, and distributed processing frameworks.
Experience with DevOps, CI/CD pipelines, and Infrastructure as Code.
Strong understanding of data governance, security, and compliance best practices.
Excellent analytical, communication, and leadership skills.

Nice To Haves

AWS Certified Solutions Architect, AWS Data Analytics Specialty, or related AWS certifications.
Familiarity with Apache Spark and distributed computing frameworks.
Experience supporting analytics, reporting, and AI/ML workloads.
Experience working in regulated industries such as utilities, energy, healthcare, or financial services.

Responsibilities

Lead and mentor a team of data engineers and ETL developers in the delivery of cloud-native data solutions.
Provide technical direction, architectural guidance, and best practices for ETL development and data integration initiatives.
Conduct design reviews, code reviews, and solution assessments to ensure scalability, maintainability, security, and performance.
Collaborate with project managers, business stakeholders, architects, and application teams to define delivery roadmaps and technical strategies.
Drive Agile/Scrum delivery processes and ensure successful execution of sprint commitments.
Design scalable, secure, and high-performance data architectures on AWS.
Architect enterprise ETL/ELT pipelines for batch and real-time data processing.
Define data ingestion, transformation, storage, and consumption patterns across structured and unstructured data sources.
Establish enterprise data modeling standards, metadata management practices, and data governance frameworks.
Develop reusable frameworks, accelerators, and reference architectures for cloud data engineering initiatives.
Design and implement ETL workflows using AWS-native services such as: AWS Glue, AWS Lambda, Amazon S3, Amazon Redshift, Amazon EMR, AWS Step Functions, Amazon Athena, Amazon RDS, AWS Lake Formation.
Build and optimize large-scale data pipelines and orchestration frameworks.
Ensure data quality, lineage, monitoring, observability, and operational supportability of ETL solutions.
Optimize cloud performance and cost efficiency across AWS data services.
Partner with business and analytics teams to translate requirements into technical solutions.
Work closely with cybersecurity, infrastructure, and enterprise architecture teams to align with organizational standards.
Provide status updates, technical documentation, and executive-level communication regarding solution delivery and risks.
Support production deployments, incident resolution, and continuous improvement initiatives.