Data Architect
Posted on 3/21/2024
Orion Innovation

1,001-5,000 employees

Digital transformation and product development services
Company Overview
Orion Innovation, a leading digital transformation and product development services firm, stands out for its extensive global reach with a team of approximately 6400 associates across North America, EMEA, APAC, and LATAM, and its proven track record of solving complex business problems for a diverse range of industries over the past 30 years. The company's competitive advantage lies in its ability to provide transformative business solutions rooted in digital strategy, experience design, and engineering, enabling clients to operate with agility at scale. Orion's impressive growth, tripling its business over the last three years, showcases its industry leadership and its commitment to being a trusted partner in accelerating digital innovation.
Consulting

Company Stage

N/A

Total Funding

N/A

Founded

1993

Headquarters

Edison, New Jersey

Growth & Insights
Headcount

6 month growth

0%

1 year growth

0%

2 year growth

0%
Locations
Encino, Los Angeles, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Microsoft Azure
NoSQL
Data Science
R
Hadoop
Data Analysis
CategoriesNew
Data Engineering
Data Management
Data Science
Data & Analytics
Requirements
  • Experience with Azure / Any Cloud and On-Prem Services Apache Spark™ Analytics, Microsoft Purview, Сloud Hadoop, R Server, HBase, and Storm clusters, Azure Stream Analytics, Azure Dev Ops, and standard Microsoft development environments
  • Experience with Data Bricks and Azure Synapse
  • Low code/No Code, ERP, APIM, Event hubs and application integration technologies
  • Experience working in various technical environments including data architecture, programming experience, preferably in building enterprise web solutions
  • Familiarity of the SDLC and common development practices
  • Bachelor’s degree in computer science or related field or equivalent experience and/or training
  • Experience in integration enterprise solutions using Services and/or APIs
  • Experience on Cloud, Relational, NoSQL and Big Data technologies, techniques, and trends
  • Strong Experience with data analytics data integration (ETL/ELT), data delivery, data preparation, data discovery, data processing, data storage, and data science
Responsibilities
  • Define software feasibility, run data reviews, assess current databases to identify areas in need of improvement, and oversee data development teams
  • Build and maintain Enterprise Data Model to meet the company’s needs
  • Understand the Industry latest trends on data strategy and create Innovative solutions
  • Provideу updates to stakeholders on product development processes
  • Drive innovation and data strategy by building and improving the data modeling and database design and best practices around Data Modeling/Architecture
  • Lead the data committee, gather requirements, and define data models and data solutions
  • Collaborate with stakeholders to understand the organization's data requirements, business objectives, and long-term goals.
  • Develop a data strategy that aligns with the overall business strategy and ensures data-driven decision-making.
  • Design and develop data models that cater to the specific needs of the organization.
  • Establish efficient and robust data integration processes to extract, transform, and load (ETL) data from various sources into the Azure environment. Ensure data quality, consistency, and accuracy during the integration process.
  • Design and implement data warehousing solutions using Azure services to enable scalable storage and efficient data retrieval for analytical processing.
  • Establish data governance policies and procedures for data access, usage, and retention.
  • Design data visualization solutions for reporting and business intelligence purposes.
  • Work closely with cross-functional teams, including developers, data engineers, business analysts, and project managers, to ensure successful implementation of data solutions.
  • Document the data architecture, data flows, and processes for reference and training purposes, enabling other team members to understand and work with the data architecture effectively.