// DATA SERVICES

Big data infrastructure that's actually usable.

We design data pipelines and warehousing that turn scattered data into something your teams can query, trust and act on.

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Reliable ETL/ELT pipelines that keep your data fresh and consistent.

Scalable warehouse architecture built for your query patterns, not a generic template.

Validation, lineage and access controls so your data can be trusted.

Event-driven pipelines for use cases that can't wait for a nightly batch job.

// OUR PROCESS

How we deliver

Requirements, constraints and success metrics defined before work starts.

Iterative delivery in two-week sprints with a reviewable milestone each time.

Testing and stakeholder review before anything reaches production.

Go-live support plus an ongoing maintenance option afterward.

// TECH & TOOLS

We pick the stack and tools that fit the problem, not a one-size-fits-all template.

Apache Spark Kafka Hadoop Snowflake Airflow Python AWS Redshift dbt

Records processed daily

★★★★★

"Our nightly batch jobs used to take 6 hours. After TurtlTech rebuilt the pipeline, it's under 40 minutes."

Data Engineering Lead

E-commerce Platform

// FAQ

How long does a typical big data pipeline project take?

Most big data pipeline engagements run 4–10 weeks depending on scope, with a working milestone reviewed every two weeks.

Do you work with our existing team or fully independently?

Both — we integrate with in-house teams as an extension, or run the engagement fully independently, based on what you need.

How is pricing structured?

Fixed scope for well-defined projects, or a sprint-based retainer for ongoing work — whichever fits the engagement better.

Do you provide support after launch?

Yes — monthly retainers cover monitoring, fixes, and incremental improvements after go-live.

We'll assess your data stack and show you the fastest path to insight.

Call +91 9958040595 info@turtltech.com