Data Engineering Services
Build the reliable, scalable pipelines that feed analytics, applications and AI.
Explore data engineering capabilities & delivery details
- Data & AI practice
- 50+ BusinessObjects clients
- AVEVA PI & OT-IT expertise
Data Engineering & Big Data at a glance
TechTiera designs and builds data platforms and pipelines: ingestion from applications, files, APIs and streams; transformation with ELT; lakehouse and data warehouse implementations on Databricks, Microsoft Fabric, Snowflake and cloud services; and big data processing with Spark. We add testing, observability and DataOps so pipelines stay reliable.
What we deliver
Data Engineering & Big Data services scoped around your platforms, processes and goals.
Data platform architecture
Design lakehouse, warehouse and streaming architectures.
Ingestion & ELT pipelines
Build batch and incremental pipelines from source systems.
Streaming & real-time data
Process events with Kafka, Event Hubs and Spark Streaming.
Big data processing
Scale transformations with Spark on Databricks and cloud services.
Data warehouse modernization
Migrate legacy warehouses to cloud platforms.
DataOps & observability
Automate testing, deployment and monitoring of pipelines.
How we deliver
A consistent, transparent delivery approach, adapted to your scope and engagement model.
Assess
Understand the current landscape, business priorities, constraints and risks, and agree measurable success criteria.
Design
Define the target architecture, scope, release plan and governance, with dependencies and decisions documented.
Build
Configure, develop, integrate and test in short iterations so stakeholders see working results early.
Transition
Plan cutover, train users and hand over runbooks and knowledge so teams can operate with confidence.
Run & improve
Support, monitor and optimize under an agreed service model, with a backlog of continuous improvements.
Related case studies
Intelligent automation for energy and power market data collection and validation
Read case study →
Intelligent web crawling and data capture for electronic components information
Read case study →
Automated regulatory data collection for U.S. oil & gas well information
Read case study →Why TechTiera
Two decades of enterprise delivery
More than 25 years implementing enterprise platforms, from strategy and implementation to long-term managed services.
Certified, specialist teams
Practice-aligned consultants and engineers with platform certifications across content, automation, data, cloud and applications.
Centers of excellence
Dedicated CoEs and innovation labs that develop reusable accelerators, frameworks and delivery standards.
Proprietary accelerators
Products such as DocOrbit, ECH360 and TestOrbit that shorten implementations and lower the cost of ownership.
Global delivery, local accountability
Delivery and service desk coverage across the Americas, Europe, the Middle East, India and Asia Pacific.
Quality you can audit
ISO 9001 and ISO 27001 certified, SEI CMM Level 3 processes and a 98% on-time delivery record.
Data Engineering & Big Data: frequently asked questions
Short, direct answers to the questions buyers ask most. Need more detail? Ask an expert
What is a data lakehouse?
A lakehouse combines low-cost data lake storage with warehouse features such as transactions, schemas and governance, so one platform serves BI and machine learning.
Which data engineering tools do you use?
Databricks, Microsoft Fabric and Azure Data Factory, Snowflake, AWS Glue, Google BigQuery, dbt, Apache Spark, Kafka and Airflow, among others.
Can you migrate our on-premises data warehouse to the cloud?
Yes. We assess workloads, redesign where needed, migrate data and pipelines, validate results and decommission the legacy platform.
How do you ensure data pipelines are reliable?
With automated tests, data quality checks, monitoring and alerting, version control and CI/CD for pipeline code.
Continue exploring
Backed by our Data & Analytics practice. Explore related platforms and delivery experience.
