E-Solutions

Data Architect

Company : E-Solutions

Location : Oaks, PA, 19456

Job Type : Full Time

Date Posted : 2 April 2026

Data Architect
Location:OAKS,PA.3 days onsite.
Contract

Imp Skills: Data Architect,Datavolt and Snowflake.

Here is the JD:

The Technical Data Architect is a leadership role. They are responsible for ensuring the use of common client architecture patterns and best practices and providing direction to the systems architects and scrum teams. The role involves leveraging cutting-edge cloud and data engineering technologies to drive high-quality and scalable solutions.

What you will do:

Design, build, and maintain enterprise data warehouse solutions using modern data warehousing methodologies, with a strong focus on Data Vault 2.0
Implement Data Vault 2.0 models, including Hubs, Links, Satellites, and downstream Information Marts, ensuring auditability, historization, and scalability
Develop and maintain Raw Vault and Business Vault layers, applying appropriate business rules and transformations where required
Design and implement dimensional data models (Star and Snowflake schemas) for analytics, reporting, and downstream consumption
Own the end-to-end data modeling lifecycle, from source analysis through conceptual, logical, and physical models
Ensure proper grain definition, conformed dimensions, and consistent business definitions across the data warehouse
Partner with business and technical stakeholders to translate requirements into scalable and maintainable data models
Architect, develop, and optimize ELT pipelines using Snowflake, Airflow, DBT, and Python, following modern cloud data warehousing best practices
Implement metadata-driven and reusable pipeline patterns to support scalability and faster onboarding of new data sources
Design and implement data quality checks, reconciliations, and validation frameworks to ensure accuracy, completeness, and consistency of warehouse data
Monitor and optimize data warehouse performance, including query execution, data volumes, and pipeline runtimes
Proactively identify and resolve data performance bottlenecks in ELT processes and analytical workloads
Ensure data pipelines support incremental loads, historization, and change data capture (CDC) patterns where applicable
Work closely with Agile teams to deliver production-ready data solutions, from design through deployment
Analyze data issues and defects, performing root-cause analysis across pipelines, models, and transformations
Mentor engineers on data warehousing best practices, Data Vault modeling, and performance optimization techniques
Ensure quality for our customers by validating Performance, Stability, Scalability, and Reliability for all of our scrum initiatives
Gain a technical and functional understanding of our product architecture and become part of the ongoing improvement of the performance of our enterprise application
Work proactively with members of an Agile team to find and fix defects in our product architecture
Analyze defects / test results and be able to deduct the chain of events leading to a failure
Communicate critical issues and status updates in a timely manner to Agile teams
Mentor technical resources on performance best practices
Deep understanding of Application Performance Monitoring and ability to develop predictive and prescriptive solutions in the big data arena

What we need from you:

BA/BS in a related technical field; or the equivalent in education and work experience
A minimum of 10 years of experience in Information Technology
A minimum of 10 years of hands-on experience in Data Warehousing, Data Engineering, and Data Architecture, with proven delivery of production-grade enterprise data platforms
Experience with data warehousing tools and technologies.
Strong, hands-on experience with Data Vault 2.0 in enterprise data warehouses, including practical implementation of Hubs, Links, and Satellites
Strong knowledge of Raw Vault, Business Vault, and Information/Data Mart design
Solid grounding in dimensional modelling (Kimball) including Star and Snowflake schemas, fact and dimension table design along with slowly changing dimensions and hybrid DW architectures.
Hands-on experience designing scalable, auditable, and historized data models that support enterprise reporting and analytics needs
Ability to hit the ground running with minimal ramp-up on DW concepts
Experience building and managing data pipelines using Snowflake, Airflow, DBT, and Python, following modern ELT patterns
Expertise in performance tuning and optimization of data warehouse workloads, pipelines, and transformations
Experience in working with Bit Bucket, Azure DevOps, GitLab, Jira, and Confluence.
Proficiency in analysis, design, and build of SQL and PL/SQL packages.
Ability to develop and implement strategies for data archiving, purging, and lifecycle management to maintain optimal performance in data warehousing environments.
Fair experience with Azure Cloud architecture, deployment, and optimization.
Proficiency in source control solutions such as GIT/GitLab and the Git flow process.
Ability to identify performance bottlenecks from issues - complement development team in speedy analysis/root cause of performance issues is preferred.
Ability to lead performance optimization efforts with a strong command of complex performance issues and the ability to direct component owners is a plus
Oracle Database performance tuning expertise
Data Analytics and Data Visualization services
Knowledge of Performance trouble shooting is preferred.
Experience effectively interacting with large development and delivery teams and application development managers who are providing full lifecycle application support in complex, heterogeneous environments
Strong understanding of SAFe
Displays Servant Leadership Skills

What we would like from you:

Experience in wealth management, investment processing, domestic and international Equity and / or Fixed Income workflows and analytics
Experience effectively interacting with large application development and delivery teams and application development managers who are providing full lifecycle application support in complex, heterogeneous environments
Experience working with senior leadership, ability to work comfortably with a wide range of people and skill sets
Data Vault 2.0 certification (e.g., Certified Data Vault 2.0 Practitioner - CDVP2 or Data Vault Alliance certification)
Knowledge of core investment processing / wealth management transaction processing, trade flow, custody & accounting, cash processing, etc.
Ability to work effectively in a team environment, with a singular commitment to the accomplishment of team results