Intellias
Our client is a leading multi‑brand technology solutions provider to business, government, education and healthcare customers in the United States, the United Kingdom and Canada. A Fortune 500 company and member of the S&P 500 Index and employs approximately 15 000 coworkers.
Requirements
5+ years
with
Azure SQL Data Warehouse / Synapse dedicated SQL pools
or similar MPP DW.
Strong
T‑SQL
skills (complex queries, DDL/DML, performance tuning).
Solid
data‑warehousing
background (facts/dimensions, SCDs, star/snowflake).
Hands‑on
ETL/ELT
experience with
Azure Data Factory / Synapse pipelines
or similar.
Working knowledge of
Microsoft Fabric
(Warehouse, Lakehouse, OneLake, Data Factory, workspaces).
Proven track record in
data platform migrations
(on‑prem or cloud → modern DW/lakehouse).
Experience
mentoring or leading engineers , defining standards and reviewing designs.
Strong communication skills; able to explain options and trade‑offs to non‑technical stakeholders.
Nice to Have
Production experience with
Fabric
(shortcuts, notebooks, Delta‑based Lakehouse workloads).
Strong
Power BI
skills (models on Fabric Warehouse/Lakehouse, Direct Lake).
DevOps/CI‑CD
for data platforms (Git integration, automated deployments).
Familiarity with
Microsoft Purview
or other catalog/lineage tools.
Microsoft certifications (Azure Data Engineer, Solutions Architect, Power BI, Fabric when available).
Responsibilities
Guide the team
through assessment of the current SQL DW/Synapse environment, dependencies, and risks.
Define the
target Fabric architecture
(Warehouse vs Lakehouse, OneLake layout, environments).
Create a
migration playbook : standards, templates, and reusable patterns for schema, data, and pipelines.
Provide
hands‑on support
on complex areas: T‑SQL refactoring, schema migration, initial & incremental loads.
Help re‑platform or design
Data Factory / pipeline
solutions in Fabric.
Establish
data validation and performance
patterns (row counts, checksums, query parity).
Set and socialize
security & governance
patterns (RBAC, RLS/CLS, sensitivity labels, dev/test/prod).
Coach, mentor, and perform
code/pipeline reviews , raising the team’s Fabric skills.
Communicate status, risks, and technical decisions to
engineering and business stakeholders .
Seniority level
Executive
Employment type
Part‑time
Job function
Consulting, Engineering, and Information Technology
Industries
IT Services and IT Consulting and IT System Data Services
#J-18808-Ljbffr
Requirements
5+ years
with
Azure SQL Data Warehouse / Synapse dedicated SQL pools
or similar MPP DW.
Strong
T‑SQL
skills (complex queries, DDL/DML, performance tuning).
Solid
data‑warehousing
background (facts/dimensions, SCDs, star/snowflake).
Hands‑on
ETL/ELT
experience with
Azure Data Factory / Synapse pipelines
or similar.
Working knowledge of
Microsoft Fabric
(Warehouse, Lakehouse, OneLake, Data Factory, workspaces).
Proven track record in
data platform migrations
(on‑prem or cloud → modern DW/lakehouse).
Experience
mentoring or leading engineers , defining standards and reviewing designs.
Strong communication skills; able to explain options and trade‑offs to non‑technical stakeholders.
Nice to Have
Production experience with
Fabric
(shortcuts, notebooks, Delta‑based Lakehouse workloads).
Strong
Power BI
skills (models on Fabric Warehouse/Lakehouse, Direct Lake).
DevOps/CI‑CD
for data platforms (Git integration, automated deployments).
Familiarity with
Microsoft Purview
or other catalog/lineage tools.
Microsoft certifications (Azure Data Engineer, Solutions Architect, Power BI, Fabric when available).
Responsibilities
Guide the team
through assessment of the current SQL DW/Synapse environment, dependencies, and risks.
Define the
target Fabric architecture
(Warehouse vs Lakehouse, OneLake layout, environments).
Create a
migration playbook : standards, templates, and reusable patterns for schema, data, and pipelines.
Provide
hands‑on support
on complex areas: T‑SQL refactoring, schema migration, initial & incremental loads.
Help re‑platform or design
Data Factory / pipeline
solutions in Fabric.
Establish
data validation and performance
patterns (row counts, checksums, query parity).
Set and socialize
security & governance
patterns (RBAC, RLS/CLS, sensitivity labels, dev/test/prod).
Coach, mentor, and perform
code/pipeline reviews , raising the team’s Fabric skills.
Communicate status, risks, and technical decisions to
engineering and business stakeholders .
Seniority level
Executive
Employment type
Part‑time
Job function
Consulting, Engineering, and Information Technology
Industries
IT Services and IT Consulting and IT System Data Services
#J-18808-Ljbffr