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# Senior Data Architect

- **Company:** 4 STAFFING INC
- **Location:** Newark, NJ, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Airflow, Amazon Web Services, Amazon S3, Big Data, Cloud Computing, Cloud Database, Cloud Engineering, Information Systems, Computer Programming, Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Security, Data Structures, Data Systems, Database Queries, Python (Programming Language), Enterprise Messaging Systems, Performance Tuning, SQL Databases, Data Streaming, Data Ingestion, Snowflake, Electronic Medical Records, Kubernetes, Information Technology, Data Lineage, AWS Glue, Integration Frameworks, Apache Kafka, Data Management, Data Pipelines, Serverless Computing
- **Published:** November 2, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-data-architect-newark-nj--63501230-3d37-40ea-ab89-093d6483902c

## About the Role

DataArchitect Data Modeling Tool, Finance, DataArchitect Data Modeling Tool, Financial Services, Cloud Computing, Cloud Architecture, Electronic Medical Records, Amazon Web Services (AWS), Amazon Simple Storage Service (S3), Data Management, Our client is seeking a highly skilled Senior Data Architect at the VP level with extensive experience in designing and implementing cloud-based data solutions for our financial services client. The ideal candidate will have a strong background in data architecture, cloud technologies, programming, and a deep understanding of the financial industry., * Bachelor's degree in Computer Science, Information Systems, or a related field.

 * 15+ years of programming experience, with at least the last five years focused on Python. Proficiency in Java is also desirable.
 * Proven experience as a Data Architect, with a track record of designing and implementing cloud-based data solutions.
 * Strong expertise in AWS cloud platforms, including services such as S3, Redshift, Aurora, Glue, EMR, EventBridge, and Lake Formation.
 * Experience with Snowflake is a must.
 * Extensive experience designing and building data ingestion and integration platforms using AWS Glue, Airflow, dbt, Matillion, etc.
 * Proficiency in SQL, data querying, and performance optimization techniques.
 * Familiarity with cloud infrastructure technologies such as containers, Kubernetes, and serverless computing.
 * Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.
 * Strong experience with data structures, data modeling, data lineage, and data catalogues.
 * Financial industry experience is a must, with asset management experience desirable.
 * Knowledge of streaming or messaging technologies like Kafka or Kinesis is desirable.
 * Certifications in cloud platforms or data management (e.g., AWS Certified Solutions Architect) are highly desirable.

If you meet these qualifications and are passionate about leveraging cloud technologies to architect data solutions in the financial services industry, we encourage you to apply for immediate consideration.

## Description

1. Cloud-Based Data Solutions: Design and implement scalable and secure cloud-based data solutions for our financial services client, with a focus on AWS cloud platforms. Utilize AWS services such as S3, Redshift, Aurora, Glue, EMR, EventBridge, and Lake Formation to architect robust data architectures.
 2. Data Ingestion and Integration: Lead the design and development of data ingestion and integration platforms (ETL/ELT) using AWS Glue, Airflow, dbt, Matillion, and other relevant technologies. Ensure efficient and reliable data pipelines for processing large volumes of data.
 3. Data Security and Compliance: Implement data security and privacy measures in compliance with industry regulations and best practices. Ensure encryption, access controls, and compliance with data protection regulations to safeguard sensitive financial data.
 4. Financial Industry Expertise: Leverage your extensive experience in the financial industry to understand business requirements and design data solutions tailored to the unique needs of asset management and other financial services sectors.
 5. Technical Leadership: Provide technical leadership and mentorship to the data engineering team. Collaborate with cross-functional teams to translate business requirements into technical solutions and drive the implementation of best practices.