Data Engineering Consulting: Pipelines, Platforms & Production-Ready Architecture
Every AI initiative, every dashboard, every analytics strategy — all of it runs on data engineering. The pipeline is the product. The architecture is the strategy. And the specialists who build it are the scarcest talent in enterprise technology. Xylity delivers pre-qualified data engineers, architects, and platform specialists through consulting-led matching. First profiles in 4.3 days.
Lakehouse Architecture
Fabric, Databricks, Snowflake. Medallion architecture, Direct Lake, Unity Catalog.
Pipeline & ETL/ELT
ADF, dbt, Airflow, Spark, Kafka. Batch and real-time at enterprise scale.
Governance & Quality
Data catalogs, lineage, quality gates, compliance frameworks, master data.
Cloud Data Platforms
Azure, AWS, GCP. Migration, modernization, and multi-cloud strategies.
Data engineering from pipeline to production
Each service area is staffed by engineers who've built and maintained production data systems — not analysts who learned SQL last quarter. Our consulting-led matching ensures every specialist we send has the exact platform depth your project requires.
Lakehouse & Data Platform Architecture
Design and build modern lakehouse architectures on Fabric, Databricks, or Snowflake. Medallion layers, semantic models, Direct Lake connectivity, and OneLake integration for unified analytics.
Fabric Consulting →ETL/ELT Pipeline Development
Production-grade data pipelines using ADF, dbt, Airflow, Spark, and custom orchestration. Incremental loads, idempotent transforms, error handling, and monitoring that actually alerts before things break.
See delivery model →Real-Time Streaming & Integration
Event-driven architectures with Kafka, Event Hubs, Spark Structured Streaming, and change data capture. Sub-second latency for dashboards, alerting, and operational analytics.
See delivery model →Data Governance & Quality
Data catalogs, lineage tracking, quality gates, access policies, and compliance frameworks. Microsoft Purview, Unity Catalog, Collibra, and custom governance implementations.
See delivery model →Cloud Migration & Modernization
Migrate from on-premises SQL Server, Oracle, Teradata, and legacy warehouses to modern cloud platforms. Assessment, planning, execution, and parallel validation for zero-downtime transitions.
Data Warehousing →Analytics Engineering
Bridge the gap between raw data and business-ready datasets. Semantic layers, metric stores, dbt models, and self-service data products that analysts can actually use without filing tickets.
Data Analytics →Deep specialists, not platform-agnostic generalists
Enterprises commit to a data platform — Fabric-centric, Databricks-centric, or Snowflake-centric. You need specialists who go deep on your chosen stack, not consultants who've read the docs once. We match to your specific platform and version.
Microsoft Fabric
Lakehouse architecture, Direct Lake, real-time analytics, Data Factory, Spark notebooks, OneLake, Power BI semantic models. Our deepest and fastest-growing specialization — Fabric architect demand is up 180% year over year.
180% YoY demand growthDatabricks
Delta Lake, Unity Catalog, MLflow, Databricks SQL, Spark optimization, Photon engine, and Delta Sharing. Lakehouse architecture from data ingestion through ML serving and governance.
Databricks Consulting →Snowflake
Data warehousing, Snowpark for Python/Java, Snowpipe streaming, dynamic tables, data sharing, and Marketplace. Multi-cloud Snowflake deployments across Azure, AWS, and GCP.
High demandAlso covering: Azure Synapse, AWS Redshift, BigQuery, Apache Spark, Kafka, dbt, Airflow, Fivetran, Informatica, Talend, and SSIS.
Data Engineering
Pipelines, governance, lakehouse
AI & Machine Learning
Models, agents, automation
Business Intelligence
Dashboards, insights, decisions
What comes after the pipeline: AI, analytics, and everything else
Data engineering isn't the destination — it's the foundation everything else runs on. Once your pipelines are clean and your architecture is governed, the entire analytics and AI stack becomes possible.
This is Xylity's strategic advantage. We don't just build the pipeline and walk away. Because our network spans 20+ technology domains, the same relationship that delivered your Fabric architect can deliver the AI engineer who builds on top of it, the Power BI developer who visualizes it, and the analytics consultant who interprets it.
Clients who start with data engineering expand into an average of 3.2 adjacent domains within 12 months. The pipeline creates the demand.
Explore AI Consulting Services →Consulting-led matching for data engineering talent
We don't send you a stack of resumes and hope one sticks. Our technical leads — who've built production data platforms themselves — assess every candidate for your specific architecture, platform version, and project stage.
Architecture Review
Our data engineering leads review your current architecture, migration targets, and team gaps to define the exact specialist profile needed.
Network Matching
We search our pre-qualified network of 5,000+ specialists for engineers with direct experience on your platform stack and industry vertical.
Scenario Interview
Candidates solve a real-world problem from your domain: a pipeline design challenge, a governance scenario, or a migration trade-off analysis.
Deploy with Safety Net
Your specialist ships production work in week one. A Xylity delivery manager monitors quality, handles escalations, and ensures continuity.
Whether you're modernizing data or filling a bench gap
Your data platform modernization needs architects who've done it before
You're migrating to Fabric, or building a Databricks lakehouse, or consolidating five siloed data warehouses into one governed platform. Your internal team is strong but stretched. You need 2–5 senior data engineers who understand your target architecture and can contribute from day one — not month two.
Start a Consulting Engagement →Your client needs a Fabric architect and your bench is empty
Fabric demand is up 180% but Fabric architects are nearly impossible to find. Your existing talent partners don't have them. Your client deadline is in three weeks. Xylity's pre-qualified network includes specialists across every data engineering platform — Fabric, Databricks, Snowflake, and legacy stacks. First profiles in 48 hours.
Scale Your Data Team →What our clients and partners ask
The pipeline is the product.
Let's build yours right.
Whether you need a Fabric architect, a Databricks lakehouse team, or a full data platform modernization — share your requirement and we'll have curated profiles in days.