Enterprise Data Architect

5 days ago

Colorado Springs, United States Creative Financial Staffing Full time
Enterprise Data Architect

Why Join this Company?
- Recognized "employer of choice" and awarded as a "Best Place to Work" in both Southern Colorado and the Denver metro area
- Recognized by Forbes as the #1 industry for 4 years in a row
- Organization is a leader in philanthropy
- Work in a beautiful office building; the Executive Administrative Assistant will receive their own office
- Current and past employees rave about the employee culture

Opportunity Summary:

The Enterprise Data Architect has an advanced understanding of the methodologies and techniques relevant to
designing, creating, deploying, and managing data architecture
The end result will enable to meet or
exceed various business strategies
This resource will work primarily on agile teams with project managers,
product owners, data engineers, business intelligence analysts, data scientists, and developers.

Day to Day as the Enterprise Data Architect

-Initiate/recommend the collection of new data sources or modification of existing data sources to
solve business problems.
-Architect database and/or data lake schemas to ensure data is stored in an efficient manner that
aligns with the business objectives and allows rapid, actionable insights.
-Consult with Data Engineers on pipeline development ensuring data mappings align with the
expected schemas.
-Consult with Data/BI analysts and Data Scientists to ensure data schemas and pipeline processing
meet the needs of downstream analytical processes.
-Design and optimize high performing data models for different consumption patterns from the
data stores (databases and/or data lakes).
-Act as subject matter expert for ALL data flowing into data warehouse/lakehouse.
-Develop partnerships with the consumers of data assets to understand business needs.
-Facilitate schema development that aligns with business definitions.
-Document how schemas map to business data sources.
-Document various architectural patterns and practices for use throughout the Data & Analytics
teams.
-Perform periodic checks to ensure Data Engineers are following best practices as documented,
including participating in code reviews on occasion.
-Work closely with the Data Governance committee in helping define data standards and policies.
Ensure any design/development adheres to the Data Governance standards/policies.
Help ensure the data integrity of data at all stages (ingestion to presentation).
Help ensure data is secure and only accessible within guidelines set forth by the Data Governance
committee.
-Increase team effectiveness by providing consulting expertise and technical mentoring across
multiple verticals.

What you will Bring

-Bachelors Degree in Information Technology, Data Analytics or something of the like
-8+ years' experience with Management Information Systems, Computer
Science, Data Analytics, or similar
4+ years' Data modeling/design/architecture experience

2+ years working with an enterprise-wide Data Governance initiative
Pref
2+ years Financial Institution experience.
-Expert-level data requirement gathering skills (the ability to glean data requirements from
various business stakeholders and subsequently ensure delivery of the expected data assets).
-Expert-level data modeling skills including demonstrated experience with:
-Relational data modeling (such as database Entity-Relationship Diagrams).
-Data Warehouse star schema modeling
Data Lake design and implementation
Data pipeline design patterns and architecture.
-Database and Data Lake access controls (such as RBAC, SQL Schema boundaries, etc.).
-Data encryption (such as SQL Always Encrypted and/or SQL TDE)
Data hashing.
-Development and maintenance of various data pipeline processes, including targeting/sourcing data to/from a wide-variety of systems and file types.
-Modern data warehouse concepts and practices.
-SQL query syntax (ANSI SQL, TSQL, or other well-known SQL implementation).
-SQL Server database administration in on-prem and Azure environments
Microsoft SQL Server Integration Services (SSIS), Azure Data Factory, or similar.
-Development tools such as Microsoft Visual Studio.
-Version control systems, preferably Azure DevOps (formerly VSTS) and TFVC and/or Git.
-Agile development processes, such as Scrum or Kanban

#INSEP2024
#ZRCFSTECH
#LI-BE1

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