Programmatic delivers AI-driven data engineering with automation, governance, and multi-cloud expertise. We build intelligent, compliant pipelines optimized for performance, scalability, and measurable business impact transforming data into trusted, actionable insights.
Data Engineering
Engineer Reliable Data Pipelines for Analytics & AI
Our engineers design and automate robust data pipelines that power real-time analytics.
We ensure high availability, quality, and performance across multi-cloud environments.
- Streamline data delivery and maximize reliability.
Why Data Engineering Is the Core of
Digital Transformation
Data engineering is the discipline that turns data chaos into clarity. It’s how raw data becomes usable, trusted, and available fueling analytics, dashboards, and machine learning models.
Empower Your Data with AI-Driven Support
We don’t just deploy data Engineering — We engineer intelligence into them.
Our Data Engineering Capabilities
We build highly automated, resilient ETL/ELT pipelines that ingest, clean, transform, and deliver data in real time.
Using Airflow, dbt, Glue, Data Factory, and Databricks, our engineers ensure pipelines that are modular, fault-tolerant, and scalable.
Seamlessly ingest batch, real-time, and streaming data from diverse sources — ERP, CRM, IoT, APIs, or legacy systems.
We use technologies like Apache Kafka, AWS Glue, Azure Data Factory, and Databricks to automate extraction, transformation, and load (ETL/ELT) processes.
Every dataset, every stream unified in motion and at rest.
We design real-time data architectures using Kafka, Flink, and Kinesis to process streaming data from sensors, apps, and events.
This enables instant insights and event-driven automation essential for personalization, IoT, and fraud detection.
Our teams architect data pipelines and warehouses using AWS, Azure, and Google Cloud services.
We optimize storage, compute, and orchestration for elasticity and cost efficiency building fully server less and scalable solutions.
Our Approach
From Raw Data to Intelligence
2026 Guide to Data Services (Data Engineering in the AI Era)
Data engineers are now automation architects enabling self-healing, self-optimizing data ecosystems.
Highlights:
- Building modular, low-latency data pipelines
- Automating ETL/ELT workflows with AI tools
- Real-time data validation and quality enforcement
CI/CD for data infrastructure (DataOps)
Why Choose Programmatic for Data Engineering?
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Get in touch.
Have a data challenge, a brilliant idea, or just curious about what we can build together? We’re ready to listen and collaborate.
Frequently Asked Questions
It includes designing, building, and managing data pipelines, integrations, models, and architecture to make data usable, reliable, and analytics-ready.
Yes we specialize in real-time streaming architectures using Kafka, Flink, and Kinesis.
We enforce encryption, IAM-based access control, audit trails, and compliance frameworks like GDPR and HIPAA.
Absolutely. We refactor legacy ETL jobs into scalable, serverless ELT pipelines with observability and CI/CD automation.