Data & Analytics

Data Engineering Company in Delhi NCR

Pyzen delivers data engineering services that connect business systems, build trusted data pipelines and prepare analytics-ready warehouses or lakehouses. Based in Delhi NCR, we work with teams in India and worldwide to scope data architecture, integration, quality and governance around real reporting and operational needs.

Plan your data project Explore services
Data & Analytics Data Engineering & Analytics
  • Pipeline development
  • Warehouse and lakehouse
  • Data modelling with dbt
  • Data quality
NDA protected · senior team · one point of contact

Transform your business with Data Engineering & Analytics

Understanding Data Engineering & Analytics

Data engineering turns data from operational systems, applications and files into reliable, usable datasets. Pyzen designs and implements data engineering services across ingestion, transformation, modelling, warehouse or lakehouse architecture, data quality and analytics integration. The right design depends on your sources, cloud environment, data volumes, security requirements and the decisions your teams need to make.

  • Pipeline development. Build and maintain batch or near-real-time ELT pipelines from databases, ERP and CRM systems, files and APIs, with schema checks, retries and operational alerts.
  • Warehouse and lakehouse. Design a warehouse or lakehouse on platforms such as Snowflake, BigQuery, Databricks or Microsoft Fabric, based on workload, governance and cloud requirements.
  • Data modelling with dbt. Transform source data into reusable models with dbt, including documented definitions, tests and lineage for analytics teams.
  • Fixed-scope discovery milestones
  • Senior engineering leads on every project
  • Transparent code ownership and delivery
Plan your data project Explore services
DiscoverScope the business need
DesignPlan the right approach
BuildImplement and validate
SupportHandover and improve

Solutions

Everything Data Engineering & Analytics teams need

Pyzen delivers data engineering services that connect business systems, build trusted data pipelines and prepare analytics-ready warehouses or lakehouses. Based in Delhi NCR, we work with teams in India and worldwide to scope data architecture, integration, quality and governance around real reporting and operational needs.

Pipeline development

Build and maintain batch or near-real-time ELT pipelines from databases, ERP and CRM systems, files and APIs, with schema checks, retries and operational alerts.

Warehouse and lakehouse

Design a warehouse or lakehouse on platforms such as Snowflake, BigQuery, Databricks or Microsoft Fabric, based on workload, governance and cloud requirements.

Data modelling with dbt

Transform source data into reusable models with dbt, including documented definitions, tests and lineage for analytics teams.

Data quality

Add checks for schema changes, freshness, completeness and agreed business rules, with exceptions routed to the team responsible for resolving them.

Analytics and reporting

Connect governed models to dashboards and analysis so reports use defined metrics, access rules and consistent data sources.

AI-ready data

Prepare approved datasets and features for machine learning workflows, with access, retention and data lineage aligned to your policies.

Problem → solution

What slows Data Engineering & Analytics teams down — and how we fix it

Notes from our Data Engineering & Analytics discovery workshops: the problems we hear most, what we do about them, and what changes as a result.

From our Data Engineering & Analytics discovery workshops. Every engagement starts by naming the real blockers.
The problem

Teams report different numbers for the same KPI

What we do

Define metric logic, ownership and source data in a documented model so agreed reports can reuse the same calculation.

One version of the truth. Tested against production benchmarks.

The problem

Teams spend time consolidating siloed data manually

What we do

Connect approved databases, business applications and files through maintainable ingestion pipelines with validation and documented transformations.

Faster answers. Tested against production benchmarks.

The problem

Reports are difficult to trust or maintain

What we do

Align dashboards with agreed business questions, model definitions, access rules and data freshness expectations before rollout.

Self-service teams. Tested against production benchmarks.

Features

Must-have features, built in

Every Data Engineering & Analytics build includes the essentials your users, teams and auditors expect.

  • Automated, monitored data pipelines
  • Row-level security and role-based access
  • Documented, tested data models
  • Scheduled reports and threshold alerts
  • Mobile-friendly dashboards
  • Usage and performance monitoring

In the field

Where our Data Engineering & Analytics software works

Hover or focus a photo to see how each solution shows up in daily operations.

Pipeline development Build and maintain batch or near-real-time ELT pipelines from databases, ERP and CRM systems, files and APIs, with schema checks, retries and operational alerts.
Warehouse and lakehouse Design a warehouse or lakehouse on platforms such as Snowflake, BigQuery, Databricks or Microsoft Fabric, based on workload, governance and cloud requirements.
Data modelling with dbt Transform source data into reusable models with dbt, including documented definitions, tests and lineage for analytics teams.
Data quality Add checks for schema changes, freshness, completeness and agreed business rules, with exceptions routed to the team responsible for resolving them.

Technology

Our Data Engineering & Analytics tech stack

Proven tools chosen for reliability, security and long-term support.

Power BI Tableau Snowflake Databricks BigQuery Apache Spark Apache Kafka dbt Python PostgreSQL
PostgreSQL Python dbt Apache Kafka Apache Spark BigQuery Databricks Snowflake Tableau Power BI

Ready to build for Data Engineering & Analytics?

Pyzen delivers data engineering services that connect business systems, build trusted data pipelines and prepare analytics-ready warehouses or lakehouses. Based in Delhi NCR, we work with teams in India and worldwide to scope data architecture, integration, quality and governance around real reporting and operational needs. Start with a free discovery call with our team.

Plan your data project →

Proof from our work

Results we have delivered

Real Pyzen projects, chosen for their relevance to Data Engineering & Analytics.

Medical AI research NDA protected
DG Rakshak

Breast Cancer Detection AI

Clinical-grade diagnostic and imaging assistance for cancer research — CNN classification combined with U-Net segmentation.

96.8% Accuracy
60% Faster diagnosis
View case study ↗
Climate tech NDA protected
Passifi Tech

Climate Data Classification

Large-scale climate intelligence and environmental classification platform for advanced data processing.

99.8% Accuracy
10x Faster analysis
View case study ↗
Insurtech solutions NDA protected
Max Life Insurance

Health Data Visualization

Secure analytics suite and health data visualisation platform for high-volume enterprise tracking.

99% Policy accuracy
5x Faster underwriting
View case study ↗

Client voices

Buyer confidence for Data Engineering & Analytics

Specific proof, direct communication and measurable delivery — in our clients’ own words.

Rated by real clients Verified reviews on Clutch ★★★★★
★★★★★
Pyzen Technologies provided us with a reliable web scraping and data automation solution for our business research needs. Their team understood the requirement clearly, managed the data extraction process professionally, and delivered accurate data on time. We were impressed with their communication, technical knowledge, and support.
Patni Art Linkers Client

FAQ

Data Engineering & Analytics questions, answered

Anything else? Ask an expert →

What data sources can your data engineering team connect?

We assess supported databases, ERP and CRM platforms, business applications, files and APIs during discovery. The integration plan depends on your access, source quality, vendor interfaces and security requirements.

How long does it take to build a data pipeline or warehouse?

Timing depends on source access, data quality, architecture, governance and the first reporting requirements. Pyzen scopes milestones after reviewing your current environment and the datasets in scope.

Which data platform should we choose for analytics?

The choice depends on your current cloud, data types, workloads, team skills, governance and cost requirements. Pyzen can assess options such as Snowflake, BigQuery, Databricks or Microsoft Fabric against your constraints.

How do we start a data engineering engagement with Pyzen?

Begin with a discovery call about the business decisions, data sources, cloud environment, security and reporting constraints. Pyzen can then scope an assessment or implementation plan with deliverables and milestones.

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Start a conversation

Let’s talk about Data Engineering & Analytics.

Emailsales@pyzenlabs.com Phone+91 99718 38777
NoidaSector 62, Uttar Pradesh
GurugramUdyog Vihar, Haryana

A senior consultant replies within one business day.