Data Engineering

Build the data foundation your AI and analytics need to thrive

Great AI starts with great data. DHD Tech provides senior data engineers from Brazil who design and build the pipelines, warehouses, and analytics platforms that power your business intelligence and machine learning initiatives. We work with modern data stack tools and can integrate with any existing infrastructure.

Data Engineering Services

From raw data ingestion to executive dashboards, we build the full data lifecycle.

  • Data Pipeline Development — Real-time and batch pipelines using Airflow, Dagster, Prefect, or custom solutions
  • Data Warehouse Design — Snowflake, BigQuery, Redshift, or Databricks architectures optimized for your query patterns
  • ETL/ELT Processes — Extract, transform, and load data from any source with dbt, Fivetran, or custom connectors
  • Data Lake Architecture — S3, GCS, or ADLS-based data lakes with proper partitioning and governance
  • Analytics & BI — Connect your data to Looker, Tableau, Metabase, or custom dashboards
  • Data Quality & Governance — Automated testing, monitoring, and lineage tracking for trusted data

Modern Data Stack Expertise

We stay current with the rapidly evolving data ecosystem and recommend tools that fit your scale, budget, and team capabilities.

  • Orchestration — Airflow, Dagster, Prefect for workflow management
  • Transformation — dbt for SQL-based transformations with testing and documentation
  • Streaming — Kafka, Kinesis, Pub/Sub for real-time data processing
  • Storage — Snowflake, BigQuery, Redshift, Databricks, PostgreSQL
  • Quality — Great Expectations, dbt tests, custom monitoring

Technologies We Use

Python SQL Apache Airflow dbt Dagster Apache Kafka Apache Spark Snowflake BigQuery Redshift Databricks Fivetran AWS Glue PostgreSQL MongoDB Looker Tableau Metabase

Frequently Asked Questions

Absolutely. We integrate with whatever tools you already use. Whether you're on Snowflake, BigQuery, a custom PostgreSQL setup, or something else entirely, our engineers have experience across the full data ecosystem.

We implement automated data quality checks at every stage of the pipeline. This includes schema validation, freshness monitoring, row count checks, and business rule validation using tools like dbt tests and Great Expectations.

Yes. We build both batch and real-time streaming pipelines using Kafka, Kinesis, or Pub/Sub depending on your cloud platform and latency requirements.

Related Services

Ready to scale your engineering team?

Tell us about your project and we'll get back to you within 24 hours.

Start a conversation