Hire data architects who design the enterprise data blueprint — platform selection (Fabric, Databricks, Snowflake), dimensional modeling, governance frameworks, and the data strategy that connects infrastructure investments to business outcomes. Data architects who design the data platform that 500 reports and 50 ML models depend on. Pre-qualified through our data strategy consulting experts.
Hire data architects because the architectural decisions made in month 1 determine whether your data platform scales or collapses in year 3. A bad dimensional model forces 200 reports to use complex workarounds. A wrong platform choice costs $500K in migration. Data architects prevent these expensive mistakes by designing the blueprint before anyone writes a pipeline.
Data architecture requires: Platform strategy — Fabric vs Databricks vs Snowflake decision framework. Dimensional modeling — star schema, conformed dimensions, bus matrix. Governance design — data ownership, classification, quality rules, access policies. Integration architecture — how 50 source systems feed the platform.
Data architects produce: Data strategy — maturity assessment, platform selection, phased roadmap with business value at each milestone. Architecture — dimensional models, integration patterns, governance frameworks, security design.
Also: Platform design — Fabric workspace structure, Databricks Unity Catalog hierarchy, Snowflake account/database/schema design. Connected to our data strategy and data governance practices.
Seniority: Senior to Principal (8-20 yrs)
Avg time to profile: 4.3 days
Engagement: 3-18+ months
Request Profiles →Your data architecture needs: current state, platform preferences, data volume, governance maturity, and business objectives.
Data architects from our network who've designed enterprise data platforms at scale.
Scenario: assess your data landscape and design the target architecture with platform recommendation.
Curated architect profiles in 4.3 days.
Pipelines, warehouses, governance.
Dashboards, reporting, self-service.
ML, AI, and advanced analytics.
4.3-day average to first curated profile. For urgent backfills, we've delivered within 48 hours from 200+ pre-qualified delivery partners.
Mid through principal level. Most data placements are senior (5-10 years) or lead (8-15 years). Specialists who build production data systems from day one.
4-stage consulting-led matching: skill assessment, scenario-based evaluation (real data problems, not SQL quizzes), reference verification, and domain review by our data engineering experts. 92% first-match acceptance rate.
Staff augmentation, project delivery, or managed capacity. 3-18+ months. Flexible scaling as data needs evolve.
Hire data architects who design enterprise data platforms — strategy, modeling, governance, and platform selection.