Data Engineering
Put enterprise data to work for the business — end-to-end data lifecycle management tailored to evolving consumption patterns.
Businesses need an efficient, agile way to source and consume data
Enterprises today have access to enormous amounts of data from multi-cloud infrastructures. Yet their ability to put that data to work is constrained by complexity, weak data management and ill-equipped infrastructure and tooling.
Overcoming these obstacles requires turning a fast-growing pool of enterprise data into actionable intelligence, building a trustworthy data foundation and proper preparation that yields insight from raw data — across interactive visualization, predictive and prescriptive analytics.
Data engineering services that accelerate digital evolution
Rapinno helps enterprises solve their data challenges, improve end-user satisfaction and guide business strategies with intelligent insights. Our teams work across structured, semi-structured and unstructured data with the right technology, processing tools and approach.
We provide complete data lifecycle management services — replacing costly, siloed in-house infrastructure and turning big-data pipelines into robust systems ready for agile business analytics.
Our data engineering services
A full toolkit covering ingestion, storage, transformation, pipelines, deployment and quality — built for legacy, big-data and cloud environments.
Data Collection & Summarization
Extract structured and unstructured data from streaming and batch sources; refine and cleanse it for legacy or cloud systems and downstream analytics.
Data Storage & ELT/ETL
Extract, transform and load across relational, NoSQL, big-data and cloud storage — chosen based on data availability, volume, velocity and type.
Data Migration
Smart, efficient migration of business data from on-prem legacy systems into cloud storage or new target platforms — minimizing risk and downtime.
Data Pipelines
Production-grade, repeatable data workflow pipelines using ADF, Databricks, Synapse, Informatica and more — supporting batch and real-time processing.
CI/CD for Data
Build and release pipelines using IaC, schema definitions, stored procedures, pipeline definitions and validation logic — across legacy and cloud.
Data Quality
Automated quality solutions for correction, enrichment, standardization and de-duplication — delivering trustworthy data to downstream consumers.
Real-time & Streaming
Event-driven streaming pipelines with Kafka, Event Hubs and Kinesis — enabling sub-second insight for operational and customer-facing use cases.
Stewardship & Compliance
Insight and intelligence on stewardship, compliance and regulatory drivers — embedded into engineering workflows from day one.
Outcomes we deliver
Faster time-to-value
Accelerators, frameworks and proven services compress delivery cycles without compromising on quality.
Improved operational efficiency
Operational data, ML/AI use cases and supply-chain visibility drive efficiency, replenishment and proactive issue resolution.
New customer & market insights
Retail and market data integration unlocks new insight into consumer behavior, inventory and channel performance.
Enhanced compliance
Regulatory and market data is integrated into sales and distribution workflows — keeping operations within tolerance.
Common questions
Which platforms and tools do you support?+
Across Azure (Fabric, Synapse, ADF), AWS (Glue, EMR, Redshift), GCP (BigQuery, Dataflow), Databricks, Snowflake and Informatica — plus open-source stacks like Spark, Kafka and Airflow.
Can you handle both batch and real-time pipelines?+
Yes. Our pipelines support batch, micro-batch and true streaming — chosen based on the consumption pattern and SLA the business needs.
How do you ensure data quality?+
We embed automated quality checks (completeness, accuracy, consistency, uniqueness) directly in pipelines, with profiling, anomaly detection and remediation workflows tied to ownership.
How do you typically engage?+
Most engagements start with a 16-week assessment and POC, followed by 1–2 years of execution and delivery, and ongoing managed data services. Commercial terms are flexible — fixed bid, T&M or managed services.
Ready to put your data to work?
Talk to our data engineering specialists about pipelines, platforms and lifecycle management built for scale.