Data Architect
T
TechtorchData and AI
United States, Poland, United KingdomFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 7+ years
- Required Skills
- SQLETLData modelingdbtGenerative AI
Requirements
- 7+ years of experience in data architecture, data engineering, or related roles in complex environments.
- Demonstrated experience designing robust technical solutions for clients or customers.
- Experience serving as a technical lead, mentoring, coaching, and setting technical direction.
- Strong background in data modeling, data warehousing (e.g., Snowflake, Redshift, BigQuery), and database design.
- Familiarity with modern data transformation practices (e.g., dbt) and dimensional modeling patterns.
- Proficiency with data modeling tools (e.g., ER/Studio, Erwin) and databases (SQL Server, Oracle, MongoDB).
- Fluent with AI coding agents (e.g., Claude Code, Cursor) and capable of evaluating and coaching others on their use.
- Skilled in applying AI/ML to complex data challenges, including generative AI and RAG architectures.
- Experience with CRM or ERP ecosystems (e.g., Salesforce, NetSuite).
- Knowledge of modern cloud data stacks (Azure, AWS, GCP).
- Hands-on experience with ETL/integration tools (e.g., Talend, Informatica).
- Familiarity with reporting solutions like Power BI or Tableau.
Responsibilities
- Develop and maintain enterprise data architecture, including models, flow diagrams, and integration frameworks.
- Define and enforce architecture standards, governance models, and documentation practices.
- Design scalable, flexible solutions that align with modern data warehousing and cloud-native best practices.
- Drive the design and implementation of data integration pipelines and APIs across systems.
- Lead efforts in data modeling, database design, and architecture optimization.
- Collaborate with data engineers, analysts, and developers to ensure architectural consistency and performance.
- Mentor and provide technical direction to engineers on the Data Practice team.
- Oversee data quality, lineage, and security strategies across the organization.
- Provide guidance on big data technologies, ETL platforms, and modern cloud ecosystems.
- Support strategic decisions through architectural reviews, proofs of concept, and solution roadmaps.
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