Data Services

Data Infrastructure Built to Last

We design and build the data infrastructure that powers your analytics and AI — scalable pipelines, cloud data warehouses, real-time streaming, and data governance frameworks.

Get Free Consultation View Our Work

100+

Data Pipelines Built

50TB+

Data Processed Daily

99.9%

Pipeline Uptime

Engineering Services

Our Data Engineering Capabilities

Every data engineering capability to build your modern data stack.

ETL/ELT Pipeline Development

Robust data pipelines using Apache Spark, dbt, Airflow, and Fivetran that reliably move and transform data at scale.

Data Warehouse Design

Scalable data warehouse architecture on Snowflake, BigQuery, and Redshift — optimised for analytics performance and cost.

Real-Time Streaming

Event streaming pipelines with Apache Kafka, AWS Kinesis, and Flink for real-time data processing and analytics.

Data Lake Architecture

Cost-effective data lakes on AWS S3, Azure Data Lake, and GCS for storing and processing large volumes of raw data.

Data Governance

Data catalogues, lineage tracking, quality monitoring, and access controls to ensure data is trustworthy and compliant.

DataOps & Automation

Automated testing, monitoring, and deployment for data pipelines — applying DevOps principles to data engineering.

Engineering Process

How We Build Your Data Platform

A structured data engineering process that delivers reliable, scalable data infrastructure.

Data Architecture Design

We design the target data architecture — warehouse, lake, or lakehouse — based on your data volume, use cases, and budget.

Pipeline Development

We build ingestion, transformation, and loading pipelines with comprehensive testing and error handling.

Quality & Governance

We implement data quality checks, monitoring, and governance controls to ensure data reliability.

Deploy & Operate

We deploy to production with full monitoring and alerting, and offer managed data operations for ongoing reliability.

FAQ

Frequently Asked Questions

What is the modern data stack?

The modern data stack typically includes a cloud data warehouse (Snowflake/BigQuery), an ELT tool (Fivetran/Airbyte), a transformation layer (dbt), and a BI tool (Looker/Tableau).

Should I use a data warehouse or data lake?

Data warehouses are best for structured analytics; data lakes for raw, unstructured data. Many organisations use a lakehouse architecture that combines both.

How do you ensure data pipeline reliability?

We implement automated testing, monitoring, alerting, retry logic, and dead letter queues to ensure pipelines run reliably and failures are caught quickly.

Can you migrate our existing data infrastructure to the cloud?

Yes. We assess your current infrastructure and execute cloud migrations with minimal disruption to your analytics operations.

Explore More

Related Services

Why Arnnima Solution

Why Businesses Choose Us for Data Engineering

We combine deep technical expertise, agile delivery, and a genuine commitment to your success — making us the partner of choice for Data Engineering across India and globally.

Talk to an Expert

Robust data pipelines handling batch and real-time streaming at petabyte scale
Modern data lakehouse architecture combining the best of data lake and warehouse
Data quality frameworks with automated validation, profiling, and lineage tracking
ELT/ETL pipeline development with full observability and automated error recovery
Data mesh and data product design for federated, domain-owned data architectures
DataOps practices bringing DevOps discipline to your data engineering lifecycle

Technologies

Our Technology Stack

We use industry-leading tools and frameworks to deliver robust, scalable Data Engineering solutions.

Orchestration

Apache Airflow Prefect Dagster dbt

Processing

Apache Spark Flink Kafka Databricks

Storage

Snowflake BigQuery Delta Lake Apache Iceberg

Industries

Industries We Serve with Data Engineering

Our Data Engineering solutions are trusted by businesses across diverse sectors.

Financial Services

Retail & CPG

Healthcare & Life Sciences

Manufacturing

Media & Advertising

Logistics & Supply Chain

Client Stories

What Our Clients Say About Our Data Engineering

Real results from real businesses who trusted Arnnima Solution with their Data Engineering needs.

"Arnnima rebuilt our data pipelines from scratch using Apache Airflow and dbt. Data freshness went from T+24 hours to T+30 minutes and pipeline failures dropped to near zero."

Preet KaurHead of Data Engineering, FinEdge Corp

"Their data lakehouse implementation on Databricks unified our fragmented data sources. Our analysts now have a single, trusted source of truth for the first time."

Marcus WebbChief Data Officer, RetailMedia UK

"The streaming pipeline they built on Kafka processes 2 million events per second. Architected for scale from day one — we haven't needed to touch it in 14 months."

Arjun BhatPlatform Engineer, TechStream India