Data Engineering & Modernization Services
Modernize, migrate, and orchestrate your data seamlessly with our Databricks expertise.
Unlock the Full Potential of Your Data
Build Smarter, Faster, and Future-Ready Data Systems
Data Engineering & Modernization is about turning your raw data into a dependable, scalable foundation that drives business outcomes. From robust pipelines to Lakehouse architectures, we help enterprises using Databricks organize, govern, and optimize their data for analytics, AI, and smarter decision-making. At Sinki.ai, our Databricks-powered solutions simplify complexity, accelerate insights, and give your teams the confidence to act on data faster, smarter, and with measurable impact.
Our Data Engineering & Modernization Services
Data Pipelines
We build reliable batch and streaming pipelines using Delta Lake and Auto Loader, ensuring your data flows efficiently from source to target, ready for analytics and AI.
Data Orchestration
Automate and manage workflows with Databricks Workflows. From job scheduling to monitoring, we ensure your pipelines run smoothly and are fully auditable.
Data Integration
Seamlessly connect diverse sources, databases, APIs, streaming data, or third-party SaaS into Databricks. We use tools like Unity Catalog and Delta Live Tables to maintain secure, consistent access.
Data Migration
We execute phased, low-risk migrations to Databricks Lakehouse architecture, utilizing tools like Auto Loader and Delta Lake to ensure data integrity, minimal downtime, and business continuity.
Data Modernization
Upgrade legacy systems with Lakehouse architecture, leveraging Delta Lake for ACID transactions, partitioning strategies for performance, decoupled compute for scalability, & cost management best practices.
Data Lakehouse Consulting
Our experts provide guidance on architecture, modeling, governance, and analytics integration, ensuring your Lakehouse is optimized for insights, BI, and AI initiatives.
Our Approach
01. Assess & Align
We begin by understanding your current data landscape, key challenges, and business goals to create a clear modernization roadmap.
02. Architect & Plan
We design a scalable, secure architecture that's tailored to your needs, from pipelines to governance and cost management.
03. Build & Migrate
Our experts develop and deploy reliable data pipelines, workflows, and integrations through a phased, low-risk implementation approach.
04. Optimize & Govern
We enhance performance, improve cost efficiency, and implement governance frameworks to keep your systems compliant and scalable.
05. Operate & Improve
Finally, we set up monitoring, alerts, and continuous improvement so your data ecosystem can evolve as your business grows.
Key Benefits
Faster Insights
Accelerate time from raw data to actionable dashboards and AI models.
Robust Governance
Maintain secure, compliant data with lineage tracking, access controls, and Unity Catalog integration.
Operational Resilience
Ensure high availability with monitoring, alerts, and automated recovery for production pipelines.
Scalable Data Architecture
Future-proof your data systems to grow with evolving business needs.
Cost Efficiency
Optimize Databricks and cloud usage to reduce operational expenses.
AI & ML Readiness
Build engineered data foundations that support ML lifecycles and MLOps.
Built on the Platforms You Trust
Why Choose us for your Data Engineering needs?
Certified Databricks Expertise
We bring deep, hands-on experience across the Databricks ecosystem, ensuring faster, more efficient deployments.
End-to-End Support
From design to deployment, we handle every stage of your data modernization journey.
Tailored Solutions
Every project is customized to fit your organization’s data landscape and business goals.
Business-Focused Approach
We align data initiatives with measurable business outcomes, not just technical changes.
Scalable & Secure Delivery
Solutions are designed for compliance, growth, and long-term sustainability.
Ready to Transform Your Data Infrastructure?
Insights & Resources
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Frequently Asked Questions
Data modernization involves upgrading legacy data systems to modern, cloud-based architectures that support real-time analytics and AI applications.
It depends on scope — a focused pipeline migration can take weeks; full platform modernization is typically a few months. We deliver a phased plan with measurable milestones to reduce risk.
Yes — by rightsizing compute, auto-scaling, and using Delta/Lakehouse patterns we regularly reduce total cost of ownership. Our optimization work targets both performance and cost.
Yes — we design and implement Unity Catalog migrations and governance models to provide secure data access, lineage, and policy controls. Absolutely — we design access policies, lineage, metadata, and support Unity Catalog migration or implementation.
We adopt shift-left testing: schema checks, unit tests for transformations (dbt patterns), assertions in Delta Live Tables (where applicable), and monitoring with alerting. We embed validation, schema enforcement, and automated testing (dbt, assertions) into pipelines, plus monitoring and alerts.
Yes — our Data Engineering practice works closely with ML engineers to support MLOps, model deployment, and production monitoring.
We implement robust data governance frameworks, encryption, and compliance measures to protect your data throughout its lifecycle.